@inproceedings{tutek-etal-2025-measuring,
  title = {Measuring Chain of Thought Faithfulness by Unlearning Reasoning Steps},
  author = {Tutek, Martin and Hashemi Chaleshtori, Fateme and Marasović, Ana and Belinkov, Yonatan},
  editor = {Christodoulopoulos, Christos and Chakraborty, Tanmoy and Rose, Carolyn and Peng, Violet},
  booktitle = {Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing},
  month = nov,
  year = {2025},
  address = {Suzhou, China},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2025.emnlp-main.504/},
  doi = {10.18653/v1/2025.emnlp-main.504},
  pages = {9935--9960},
  isbn = {979-8-89176-332-6},
  abstract = {When prompted to think step-by-step, language models (LMs) produce a chain of thought (CoT), a sequence of reasoning steps that the model supposedly used to produce its prediction. Despite much work on CoT prompting, it is unclear if reasoning verbalized in a CoT is faithful to the models' parametric beliefs. We introduce a framework for measuring parametric faithfulness of generated reasoning and propose Faithfulness by Unlearning Reasoning steps (FUR), an instance of this framework. FUR erases information contained in reasoning steps from model parameters and measures faithfulness as the resulting effect on the model{'}s prediction. Our experiments with four LMs and five multi-choice question answering (MCQA) datasets show that FUR is frequently able to precisely change the underlying models' prediction for a given instance by unlearning key steps, indicating when a CoT is parametrically faithful. Further analysis shows that CoTs generated by models post-unlearning support different answers, hinting at a deeper effect of unlearning.},
  month_numeric = {11}
}

@inproceedings{woo-etal-2025-briefme,
  title = {{B}rief{M}e: A Legal {NLP} Benchmark for Assisting with Legal Briefs},
  author = {Woo, Jesse and Hashemi Chaleshtori, Fateme and Marasović, Ana and Marino, Kenneth},
  editor = {Che, Wanxiang and Nabende, Joyce and Shutova, Ekaterina and Pilehvar, Mohammad Taher},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2025},
  month = jul,
  year = {2025},
  address = {Vienna, Austria},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2025.findings-acl.681/},
  doi = {10.18653/v1/2025.findings-acl.681},
  pages = {13139--13190},
  isbn = {979-8-89176-256-5},
  abstract = {A core part of legal work that has been underexplored in Legal NLP is the writing and editing of legal briefs. This requires not only a thorough understanding of the law of a jurisdiction, from judgments to statutes, but also the ability to make new arguments to try to expand the law in a new direction and make novel and creative arguments that are persuasive to judges. To capture and evaluate these legal skills in language models, we introduce BRIEFME, a new dataset focused on legal briefs. It contains three tasks for language models to assist legal professionals in writing briefs: argument summarization, argument completion, and case retrieval. In this work, we describe the creation of these tasks, analyze them, and show how current models perform. We see that today{'}s large language models (LLMs) are already quite good at the summarization and guided completion tasks, even beating human-generated headings. Yet, they perform poorly on other tasks in our benchmark: realistic argument completion and retrieving relevant legal cases. We hope this dataset encourages more development in Legal NLP in ways that will specifically aid people in performing legal work.},
  month_numeric = {7}
}

@article{richardson2024understanding,
  title = {Understanding the Logic of Direct Preference Alignment through Logic},
  author = {Richardson, Kyle and Srikumar, Vivek and Sabharwal, Ashish},
  journal = {arXiv preprint arXiv:2412.17696},
  year = {2024},
  month = dec,
  url = {https://arxiv.org/abs/2412.17696},
  month_numeric = {12}
}

@article{chang2024main,
  title = {MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation},
  author = {Chang, Chia-Yuan and Jiang, Zhimeng and Rakesh, Vineeth and Pan, Menghai and Yeh, Chin-Chia Michael and Wang, Guanchu and Hu, Mingzhi and Xu, Zhichao and Zheng, Yan and Das, Mahashweta and others},
  journal = {arXiv preprint arXiv:2501.00332},
  year = {2024},
  month = dec,
  url = {https://arxiv.org/abs/2501.00332},
  month_numeric = {12}
}

@article{xu2024state,
  title = {State Space Models are Strong Text Rerankers},
  author = {Xu, Zhichao and Yan, Jinghua and Gupta, Ashim and Srikumar, Vivek},
  journal = {arXiv preprint arXiv:2412.14354},
  year = {2024},
  month = dec,
  url = {https://arxiv.org/abs/2412.14354},
  month_numeric = {12}
}

@article{mohanty2024crystext,
  title = {CrysText: A Generative AI Approach for Text-Conditioned Crystal Structure Generation using LLM},
  author = {Mohanty, Trupti and Mehta, Maitrey and Sayeed, Hasan M and Srikumar, Vivek and Sparks, Taylor D},
  year = {2024},
  month = dec,
  url = {https://chemrxiv.org/engage/chemrxiv/article-details/6753874c7be152b1d02eecb5},
  month_numeric = {12}
}

@inproceedings{gupta-etal-2024-enhancing,
  title = {Enhancing Question Answering on Charts Through Effective Pre-training Tasks},
  author = {Gupta, Ashim and Gupta, Vivek and Zhang, Shuo and He, Yujie and Zhang, Ning and Shah, Shalin},
  editor = {Belinkov, Yonatan and Kim, Najoung and Jumelet, Jaap and Mohebbi, Hosein and Mueller, Aaron and Chen, Hanjie},
  booktitle = {Proceedings of the 7th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP},
  month = nov,
  year = {2024},
  address = {Miami, Florida, US},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2024.blackboxnlp-1.11/},
  doi = {10.18653/v1/2024.blackboxnlp-1.11},
  pages = {185--192},
  abstract = {To completely understand a document, the use of textual information is not enough. Understanding visual cues, such as layouts and charts, is also required. While the current state-of-the-art approaches for document understanding (both OCR-based and OCR-free) work well, a thorough analysis of their capabilities and limitations has not yet been performed. Therefore, in this work, we addresses the limitation of current VisualQA models when applied to charts and plots. To investigate shortcomings of the state-of-the-art models, we conduct a comprehensive behavioral analysis, using ChartQA as a case study. Our findings indicate that existing models particularly underperform in answering questions related to the chart`s structural and visual context, as well as numerical information. To address these issues, we propose three simple pre-training tasks that enforce the existing model in terms of both structural-visual knowledge, as well as its understanding of numerical questions. We evaluate our pre-trained model (called MatCha-v2) on three chart datasets - both extractive and abstractive question datasets - and observe that it achieves an average improvement of 1.7 {\%} over the baseline model.},
  month_numeric = {11}
}

@inproceedings{xu-jiang-2024-multi,
  title = {Multi-dimensional Evaluation of Empathetic Dialogue Responses},
  author = {Xu, Zhichao and Jiang, Jiepu},
  editor = {Al-Onaizan, Yaser and Bansal, Mohit and Chen, Yun-Nung},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2024},
  month = nov,
  year = {2024},
  address = {Miami, Florida, USA},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2024.findings-emnlp.113/},
  doi = {10.18653/v1/2024.findings-emnlp.113},
  pages = {2066--2087},
  abstract = {Empathy is critical for effective and satisfactory conversational communication. Prior efforts to measure conversational empathy mostly focus on expressed communicative intents{---}that is, the way empathy is expressed. Yet, these works ignore the fact that conversation is also a collaboration involving both speakers and listeners. In contrast, we propose a multi-dimensional empathy evaluation framework to measure both expressed intents from the speaker`s perspective and perceived empathy from the listener`s perspective. We apply our analytical framework to examine internal customer-service dialogues. We find the two dimensions (expressed intent types and perceived empathy) are interconnected, while perceived empathy has high correlations with dialogue satisfaction levels.To reduce the annotation cost, we explore different options to automatically measure conversational empathy: prompting LLMs and training language model-based classifiers. Our experiments show that prompting methods with even popular models like GPT-4 and Flan family models perform relatively poorly on both public and our internal datasets. In contrast, instruction-finetuned classifiers based on FlanT5 family models outperform prior works and competitive baselines. We conduct a detailed ablation study to give more insights into instruction finetuning method`s strong performance.},
  month_numeric = {11}
}

@inproceedings{xu-etal-2024-beyond-perplexity,
  title = {Beyond Perplexity: Multi-dimensional Safety Evaluation of {LLM} Compression},
  author = {Xu, Zhichao and Gupta, Ashim and Li, Tao and Bentham, Oliver and Srikumar, Vivek},
  editor = {Al-Onaizan, Yaser and Bansal, Mohit and Chen, Yun-Nung},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2024},
  month = nov,
  year = {2024},
  address = {Miami, Florida, USA},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2024.findings-emnlp.901/},
  doi = {10.18653/v1/2024.findings-emnlp.901},
  pages = {15359--15396},
  abstract = {Increasingly, model compression techniques enable large language models (LLMs) to be deployed in real-world applications. As a result of this momentum towards local deployment, compressed LLMs will interact with a large population. Prior work on compression typically prioritize preserving perplexity, which is directly analogous to training loss. The impact of compression method on other critical aspects of model behavior{---}particularly safety{---}requires systematic assessment. To this end, we investigate the impact of model compression along four dimensions: (1) degeneration harm, i.e., bias and toxicity in generation; (2) representational harm, i.e., biases in discriminative tasks; (3) dialect bias; and (4) language modeling and downstream task performance. We examine a wide spectrum of LLM compression techniques, including unstructured pruning, semi-structured pruning, and quantization. Our analysis reveals that compression can lead to unexpected consequences. Although compression may unintentionally alleviate LLMs' degeneration harm, it can still exacerbate representational harm. Furthermore, increasing compression produces a divergent impact on different protected groups. Finally, different compression methods have drastically different safety impacts: for example, quantization mostly preserves bias while pruning degrades quickly. Our findings underscore the importance of integrating safety assessments into the development of compressed LLMs to ensure their reliability across real-world applications.},
  month_numeric = {11}
}

@inproceedings{hashemi-chaleshtori-etal-2024-evaluating,
  title = {On Evaluating Explanation Utility for Human-{AI} Decision Making in {NLP}},
  author = {Hashemi Chaleshtori, Fateme and Ghosal, Atreya and Gill, Alexander and Bambroo, Purbid and Marasović, Ana},
  editor = {Al-Onaizan, Yaser and Bansal, Mohit and Chen, Yun-Nung},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2024},
  month = nov,
  year = {2024},
  address = {Miami, Florida, USA},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2024.findings-emnlp.439/},
  doi = {10.18653/v1/2024.findings-emnlp.439},
  pages = {7456--7504},
  abstract = {Is explainability a false promise? This debate has emerged from the insufficient evidence that explanations help people in situations they are introduced for. More human-centered, application-grounded evaluations of explanations are needed to settle this. Yet, with no established guidelines for such studies in NLP, researchers accustomed to standardized proxy evaluations must discover appropriate measurements, tasks, datasets, and sensible models for human-AI teams in their studies. To aid with this, we first review existing metrics suitable for application-grounded evaluation. We then establish criteria to select appropriate datasets, and using them, we find that only 4 out of over 50 datasets available for explainability research in NLP meet them. We then demonstrate the importance of reassessing the state of the art to form and study human-AI teams: teaming people with models for certain tasks might only now start to make sense, and for others, it remains unsound. Finally, we present the exemplar studies of human-AI decision-making for one of the identified tasks {---} verifying the correctness of a legal claim given a contract. Our results show that providing AI predictions, with or without explanations, does not cause decision makers to speed up their work without compromising performance. We argue for revisiting the setup of human-AI teams and improving automatic deferral of instances to AI, where explanations could play a useful role.},
  month_numeric = {11}
}

@article{kuo2024identification,
  title = {Identification of cultural conversations in therapy using natural language processing models.},
  author = {Kuo, Patty B and Mehta, Maitrey and Hashtpari, Halleh and Srikumar, Vivek and Tanana, Michael J and Tao, Karen W and Drinane, Joanna M and Van-Epps, Jake and Imel, Zac E},
  journal = {Psychotherapy},
  year = {2024},
  publisher = {Educational Publishing Foundation},
  month = oct,
  url = {https://psycnet.apa.org/record/2025-35447-001},
  month_numeric = {10}
}

@inproceedings{10.1145/3627673.3679804,
  author = {Zhong, Da and Wang, Xiuling and Xu, Zhichao and Xu, Jun and Wang, Wendy Hui},
  title = {Interaction-level Membership Inference Attack against Recommender Systems with Long-tailed Distribution},
  year = {2024},
  isbn = {9798400704369},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3627673.3679804},
  doi = {10.1145/3627673.3679804},
  abstract = {Recommender systems (RSs) are susceptible to Interaction-level Membership Inference Attacks (IMIAs), which aim to determine whether specific user-item interactions are present in the training data of the target RS. However, existing IMIAs struggle with inferring the membership of tail interactions, i.e., the interactions involving tail items, due to the limited information available about these items. This paper introduces MINER, a new IMIA designed to enhance attack performance against RSs with long-tailed item distribution. MINER addresses the information scarcity of tail items at both the feature and sample levels. At the feature level, MINER leverages the Knowledge Graphs (KGs) to obtain the auxiliary knowledge of tail items. At the sample level, MINER designs a Bilateral-Branch Network (BBN) as the attack model. The BBN trains two branches independently, with one branch trained on interaction samples with the original long-tailed item distribution and the other on interaction samples with a more balanced item distribution. The outputs of the two branches are aggregated using a cumulative learning component. Our experimental results demonstrate that MINER significantly enhances the attack accuracy of IMIA, especially for tail interactions. Beyond attack design, we design a defense mechanism named RGL to defend against MINER. Empirical evaluations demonstrate that RGL effectively mitigates the privacy risks posed by MINER while preserving recommendation accuracy. Our code is available at https://github.com/dzhong2/MINER.},
  booktitle = {Proceedings of the 33rd ACM International Conference on Information and Knowledge Management},
  pages = {3433–3442},
  numpages = {10},
  keywords = {long-tailed distribution, membership inference attack, privacy of machine learning, recommender system},
  location = {Boise, ID, USA},
  series = {CIKM '24},
  month = oct,
  month_numeric = {10}
}

@inproceedings{10.1145/3664190.3672508,
  author = {Xu, Zhichao and Lamba, Hemank and Ai, Qingyao and Tetreault, Joel and Jaimes, Alex},
  title = {CFE2: Counterfactual Editing for Search Result Explanation},
  year = {2024},
  isbn = {9798400706813},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3664190.3672508},
  doi = {10.1145/3664190.3672508},
  abstract = {Search Result Explanation (SeRE) aims to improve search sessions' effectiveness and efficiency by helping users interpret documents' relevance. Existing works mostly focus on factual explanation, i.e. to find/generate supporting evidence about documents' relevance to search queries. However, research in cognitive sciences has shown that human explanations are contrastive i.e. people explain an observed event using some counterfactual events; such explanations reduce cognitive load and provide actionable insights. Though already proven effective in machine learning and NLP communities, there lacks a strict formulation on how counterfactual explanations should be defined and structured, in the context of web search. In this paper, we first discuss the possible formulation of counterfactual explanations in the IR context. Next, we formulate a suite of desiderata for counterfactual explanation in SeRE task and corresponding automatic metrics. With this desiderata, we propose a method named CounterFactual Editing for Search Research Explanation (CFE2). CFE2 provides pairwise counterfactual explanations for document pairs within a search engine result page. Our experiments on five public search datasets demonstrate that CFE2can significantly outperform baselines in both automatic metrics and human evaluations.},
  booktitle = {Proceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval},
  pages = {145–155},
  numpages = {11},
  keywords = {counterfactual explanation, information retrieval},
  location = {Washington DC, USA},
  series = {ICTIR '24},
  month = aug,
  month_numeric = {8}
}

@inproceedings{10.1145/3641525.3663625,
  author = {Zheng, Guineng and Ricci, Robert and Srikumar, Vivek},
  title = {LogFlux: A Software Suite for Replicating Results in Automated Log Parsing},
  year = {2024},
  month = jul,
  isbn = {9798400705304},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3641525.3663625},
  doi = {10.1145/3641525.3663625},
  abstract = {Logging mechanisms are a cornerstone in the development and maintenance of computer systems, gaining even greater prominence in the era of large-scale cloud-based applications. Their critical role in real-time system monitoring and behavior analysis cannot be overstated, making them invaluable tools for system administrators and developers alike. Automated parsing of log messages—turning the text of log messages into parsed, structured data—is a significant research area. Despite the number of log parsers that have emerged over the years, there has been a noticeable gap in the evaluation of these tools, reproduction of results, and direct comparisons between them on a level playing field. Recognizing this, we re-implemented twelve of the most popular log parsers from scratch, enabling them to be used in replication studies. This paper presents our open-source project LogFlux, which is a suite for evaluating automated log parsers so that studies involving them can be replicated. Through LogFlux, we aim to bridge the gap between theoretical log parsing methods and their practical application, offering a robust and easy to use solution that is accessible and effective for a range of users. Our experience in attempting to obtain results from many published log parser algorithms has shed light on important aspects of replication, such as the value of independent implementation for uncovering bugs and the need for careful software engineering to facilitate maintenance.},
  booktitle = {Proceedings of the 2nd ACM Conference on Reproducibility and Replicability},
  pages = {64–74},
  numpages = {11},
  keywords = {Implementations, Log Parsing},
  location = {Rennes, France},
  series = {ACM REP '24},
  month_numeric = {7}
}

@article{bentham2024chainofthought,
  title = {Chain-of-Thought Unfaithfulness as Disguised Accuracy},
  author = {Bentham, Oliver and Stringham, Nathan and Marasović, Ana},
  journal = {Transactions on Machine Learning Research},
  issn = {2835-8856},
  month = jul,
  year = {2024},
  url = {https://openreview.net/forum?id=ydcrP55u2e},
  note = {Reproducibility Certification},
  month_numeric = {7}
}

@article{gupta2024empirical,
  title = {An Empirical Investigation of Matrix Factorization Methods for Pre-trained Transformers},
  author = {Gupta, Ashim and Saravani, Sina Mahdipour and Sadayappan, P and Srikumar, Vivek},
  journal = {arXiv preprint arXiv:2406.11307},
  year = {2024},
  month = jun,
  url = {https://arxiv.org/abs/2406.11307},
  month_numeric = {6}
}

@inproceedings{gupta-etal-2024-whispers,
  title = {Whispers of Doubt Amidst Echoes of Triumph in {NLP} Robustness},
  author = {Gupta, Ashim and Rajendhran, Rishanth and Stringham, Nathan and Srikumar, Vivek and Marasović, Ana},
  editor = {Duh, Kevin and Gomez, Helena and Bethard, Steven},
  booktitle = {Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)},
  month = jun,
  year = {2024},
  address = {Mexico City, Mexico},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2024.naacl-long.310},
  doi = {10.18653/v1/2024.naacl-long.310},
  pages = {5533--5590},
  abstract = {*Do larger and more performant models resolve NLP{'}s longstanding robustness issues?* We investigate this question using over 20 models of different sizes spanning different architectural choices and pretraining objectives. We conduct evaluations using (a) out-of-domain and challenge test sets, (b) behavioral testing with CheckLists, (c) contrast sets, and (d) adversarial inputs. Our analysis reveals that not all out-of-domain tests provide insight into robustness. Evaluating with CheckLists and contrast sets shows significant gaps in model performance; merely scaling models does not make them adequately robust. Finally, we point out that current approaches for adversarial evaluations of models are themselves problematic: they can be easily thwarted, and in their current forms, do not represent a sufficiently deep probe of model robustness. We conclude that not only is the question of robustness in NLP as yet unresolved, but even some of the approaches to measure robustness need to be reassessed.},
  month_numeric = {6}
}

@inproceedings{xu-etal-2024-context,
  title = {In-Context Example Ordering Guided by Label Distributions},
  author = {Xu, Zhichao and Cohen, Daniel and Wang, Bei and Srikumar, Vivek},
  editor = {Duh, Kevin and Gomez, Helena and Bethard, Steven},
  booktitle = {Findings of the Association for Computational Linguistics: NAACL 2024},
  month = jun,
  year = {2024},
  address = {Mexico City, Mexico},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2024.findings-naacl.167},
  doi = {10.18653/v1/2024.findings-naacl.167},
  pages = {2623--2640},
  abstract = {By allowing models to predict without task-specific training, in-context learning (ICL) with pretrained LLMs has enormous potential in NLP. However, a number of problems persist in ICL. In particular, its performance is sensitive to the choice and order of in-context examples. Given the same set of in-context examples with different orderings, model performance may vary from near random to near state-of-the-art. In this work, we formulate in-context example ordering as an optimization problem. We examine three problem settings that differ in the assumptions they make about what is known about the task. Inspired by the idea of learning from label proportions, we propose two principles for in-context example ordering guided by model{'}s probability predictions. We apply our proposed principles to thirteen text classification datasets and nine different autoregressive LLMs with 700M to 13B parameters. We demonstrate that our approach outperforms the baselines by improving the classification accuracy, reducing model miscalibration, and also by selecting better in-context examples.},
  month_numeric = {6}
}

@inproceedings{mehta-etal-2024-promptly,
  title = {Promptly Predicting Structures: The Return of Inference},
  author = {Mehta, Maitrey and Pyatkin, Valentina and Srikumar, Vivek},
  editor = {Duh, Kevin and Gomez, Helena and Bethard, Steven},
  booktitle = {Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)},
  month = jun,
  year = {2024},
  address = {Mexico City, Mexico},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2024.naacl-long.7},
  doi = {10.18653/v1/2024.naacl-long.7},
  pages = {112--130},
  abstract = {Prompt-based methods have been used extensively across NLP to build zero- and few-shot label predictors. Many NLP tasks are naturally structured: that is, their outputs consist of multiple labels which constrain each other. Annotating data for such tasks can be cumbersome. Can the promise of the prompt-based paradigm be extended to such structured outputs? In this paper, we present a framework for constructing zero- and few-shot linguistic structure predictors. Our key insight is that we can use structural constraints{---}and combinatorial inference derived from them{---}to filter out inconsistent structures predicted by large language models. We instantiated this framework on two structured prediction tasks, and five datasets. Across all cases, our results show that enforcing consistency not only constructs structurally valid outputs, but also improves performance over the unconstrained variants.},
  month_numeric = {6}
}

@inproceedings{jobanputra-etal-2024-universal,
  title = {A {U}niversal {D}ependencies Treebank for {G}ujarati},
  author = {Jobanputra, Mayank and Mehta, Maitrey and Çöltekin, Çağrı},
  editor = {Bhatia, Archna and Bouma, Gosse and Doğruöz, A. Seza and Evang, Kilian and Garcia, Marcos and Giouli, Voula and Han, Lifeng and Nivre, Joakim and Rademaker, Alexandre},
  booktitle = {Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024},
  month = may,
  year = {2024},
  address = {Torino, Italia},
  publisher = {ELRA and ICCL},
  url = {https://aclanthology.org/2024.mwe-1.9},
  pages = {56--62},
  abstract = {The Universal Dependencies (UD) project has presented itself as a valuable platform to develop various resources for the languages of the world. We present and release a sample treebank for the Indo-Aryan language of Gujarati {--} a widely spoken language with little linguistic resources. This treebank is the first labeled dataset for dependency parsing in the language and the script (the Gujarati script). The treebank contains 187 part-of-speech and dependency annotated sentences from diverse genres. We discuss various idiosyncratic examples, annotation choices and present an elaborate corpus along with agreement statistics. We see this work as a valuable resource and a stepping stone for research in Gujarati Computational Linguistics.},
  month_numeric = {5}
}

@inproceedings{wang2024depth,
  title = {An in-depth investigation of user response simulation for conversational search},
  author = {Wang, Zhenduo and Xu, Zhichao and Srikumar, Vivek and Ai, Qingyao},
  booktitle = {Proceedings of the ACM on Web Conference 2024},
  pages = {1407--1418},
  year = {2024},
  month = apr,
  url = {https://dl.acm.org/doi/10.1145/3589334.3645447},
  month_numeric = {4}
}

@article{xu2024rankmamba,
  title = {RankMamba, Benchmarking Mamba's Document Ranking Performance in the Era of Transformers},
  author = {Xu, Zhichao},
  journal = {arXiv preprint arXiv:2403.18276},
  year = {2024},
  month = mar,
  url = {https://arxiv.org/abs/2403.18276},
  month_numeric = {3}
}

@inproceedings{johnson-marasovic-2023-much,
  title = {How Much Consistency Is Your Accuracy Worth?},
  author = {Johnson, Jacob K. and Marasović, Ana},
  editor = {Belinkov, Yonatan and Hao, Sophie and Jumelet, Jaap and Kim, Najoung and McCarthy, Arya and Mohebbi, Hosein},
  booktitle = {Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP},
  month = dec,
  year = {2023},
  address = {Singapore},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2023.blackboxnlp-1.19},
  pages = {250--260},
  abstract = {Contrast set consistency is a robustness measurement that evaluates the rate at which a model correctly responds to all instances in a bundle of minimally different examples relying on the same knowledge. To draw additional insights, we propose to complement consistency with relative consistency{---}the probability that an equally accurate model would surpass the consistency of the proposed model, given a distribution over possible consistencies. Models with 100{\%} relative consistency have reached a consistency peak for their accuracy. We reflect on prior work that reports consistency in contrast sets and observe that relative consistency can alter the assessment of a model{'}s consistency compared to another. We anticipate that our proposed measurement and insights will influence future studies aiming to promote consistent behavior in models.},
  month_numeric = {12}
}

@inproceedings{zhuang2023eliciting,
  author = {Zhuang, Yuan and Riloff, Ellen},
  title = {Eliciting Affective Events from Language Models by Multiple View Co-prompting},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2023},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.findings-acl.199}
}

@inproceedings{wang2023elaboration-generating,
  author = {Wang, Wenya and Srikumar, Vivek and Hajishirzi, Hannaneh and Smith, Noah A.},
  title = {Elaboration-Generating Commonsense Question Answering at Scale},
  booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.acl-long.90}
}

@article{srikumar2023integer,
  author = {Srikumar, Vivek and Roth, Dan},
  title = {The Integer Linear Programming Inference Cookbook},
  journal = {arXiv preprint arXiv:2307.00171},
  year = {2023},
  tags = {},
  paper = {https://arxiv.org/abs/2307.00171}
}

@article{rathore2023topobert,
  author = {Rathore, Archit and Zhou, Yichu and Srikumar, Vivek and Wang, Bei},
  title = {TopoBERT: Exploring the topology of fine-tuned word representations},
  journal = {Information Visualization},
  year = {2023},
  volume = {22},
  tags = {},
  paper = {https://doi.org/10.1177/14738716231168671}
}

@inproceedings{pyatkin2023clarifydelphi,
  author = {Pyatkin, Valentina and Hwang, Jena D. and Srikumar, Vivek and Lu, Ximing and Jiang, Liwei and Choi, Yejin and Bhagavatula, Chandra},
  title = {{C}larify{D}elphi: Reinforced Clarification Questions with Defeasibility Rewards for Social and Moral Situations},
  booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.acl-long.630}
}

@inproceedings{mehta2023verifying,
  author = {Mehta, Maitrey and Srikumar, Vivek},
  title = {Verifying Annotation Agreement without Multiple Experts: A Case Study with {G}ujarati {SNACS}},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2023},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.findings-acl.696}
}

@inproceedings{medinagrespan2023logic-driven,
  author = {Medina Grespan, Mattia and Broadbent, Meghan and Zhang, Xinyao and Axford, Katherine and Kious, Brent and Imel, Zac and Srikumar, Vivek},
  title = {Logic-driven Indirect Supervision: An Application to Crisis Counseling},
  booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.acl-long.654}
}

@inproceedings{khincha2023infosync,
  author = {Khincha, Siddharth and Jain, Chelsi and Gupta, Vivek and Kataria, Tushar and Zhang, Shuo},
  title = {{I}nfo{S}ync: Information Synchronization across Multilingual Semi-structured Tables},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2023},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.findings-acl.159}
}

@inproceedings{jiang2023exploiting,
  author = {Jiang, Tianyu and Riloff, Ellen},
  title = {Exploiting Commonsense Knowledge about Objects for Visual Activity Recognition},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2023},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.findings-acl.457}
}

@inproceedings{hessel2023do-androids,
  author = {Hessel, Jack and Marasović, Ana and Hwang, Jena D. and Lee, Lillian and Da, Jeff and Zellers, Rowan and Mankoff, Robert and Choi, Yejin},
  title = {Do Androids Laugh at Electric Sheep? Humor {``}Understanding{''} Benchmarks from The New Yorker Caption Contest},
  booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.acl-long.41},
  award = {Best Paper Award}
}

@inproceedings{gupta2023dont-retrain,
  author = {Gupta, Ashim and Blum, Carter and Choji, Temma and Fei, Yingjie and Shah, Shalin and Vempala, Alakananda and Srikumar, Vivek},
  title = {Don{'}t Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text},
  booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2023},
  tags = {},
  paper = {https://aclanthology.org/2023.acl-long.781}
}

@article{broadbent2023machine,
  author = {Broadbent, Meghan and Medina Grespan, Mattia and Axford, Katherine and Zhang, Xinyao and Srikumar, Vivek and Kious, Brent and Imel, Zac},
  title = {A machine learning approach to identifying suicide risk among text-based crisis counseling encounters},
  journal = {Frontiers in psychiatry},
  year = {2023},
  volume = {14},
  tags = {},
  paper = {https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1110527/full}
}

@article{li2023learning,
  title = {Learning Semantic Role Labeling from Compatible Label Sequences},
  author = {Li, Tao and Kazeminejad, Ghazaleh and Brown, Susan W. and Palmer, Martha and Srikumar, Vivek},
  year = {2023},
  eprint = {2305.14600},
  archiveprefix = {arXiv},
  primaryclass = {cs.CL},
  paper = {https://arxiv.org/abs/2305.14600}
}

@article{singhal2023intendd,
  title = {IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery},
  author = {Singhal, Bhavuk and Gupta, Ashim and P, Shivasankaran V and Krishna, Amrith},
  year = {2023},
  eprint = {2310.16761},
  archiveprefix = {arXiv},
  primaryclass = {cs.CL},
  paper = {https://arxiv.org/abs/2310.16761}
}

@inproceedings{chaleshtori2023on,
  title = {On Evaluating Explanation Utility for Human-{AI} Decision-Making in {NLP}},
  author = {Chaleshtori, Fateme Hashemi and Ghosal, Atreya and Marasović, Ana},
  booktitle = {XAI in Action: Past, Present, and Future Applications},
  year = {2023},
  url = {https://openreview.net/forum?id=8BR8EaWNTZ}
}

@inproceedings{zhou2022closer,
  author = {Zhou, Yichu and Srikumar, Vivek},
  title = {{A Closer Look at How Fine-tuning Changes BERT}},
  booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2022},
  tags = {Probing representations and models,Representations & Learning},
  paper = {pdfs/zhou2022closer.pdf}
}

@inproceedings{mehta2022psychotherapy,
  author = {Mehta, Maitrey and Caperton, Derek and Axford, Katherine and Weitzman, Lauren and Atkins, David and Srikumar, Vivek and Imel, Zac},
  title = {{Psychotherapy is Not One Thing: Simultaneous Modeling of Different Therapeutic Approaches}},
  booktitle = {Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology},
  year = {2022},
  tags = {Clinical Psychology & Technology},
  paper = {pdfs/mehta2022psychotherapy.pdf}
}

@inproceedings{gupta2022right-for,
  author = {Gupta, Vivek and Zhang, Shuo and Vempala, Alakananda and He, Yujie and Choji, Temma and Srikumar, Vivek},
  title = {{Right for the Right Reason: Evidence Extraction for Trustworthy Tabular Reasoning}},
  booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2022},
  tags = {Textual entailment,Probing representations and models},
  paper = {pdfs/gupta2022right-for.pdf}
}

@article{gupta2022is-my-model,
  author = {Gupta, Vivek and Bhat, Riyaz A and Ghosal, Atreya and Shrivastava, Manish and Singh, Maneesh and Srikumar, Vivek},
  title = {{Is My Model Using The Right Evidence? Systematic Probes for Examining Evidence-Based Tabular Reasoning}},
  journal = {Transactions of the Association for Computational Linguistics},
  year = {2022},
  volume = {10},
  tags = {Probing representations and models,Textual entailment},
  paper = {pdfs/gupta2022is-my-model.pdf}
}

@inproceedings{liu2022putting,
  author = {Liu, Yang Janet and Hwang, Jena D. and Schneider, Nathan and Srikumar, Vivek},
  title = {{Putting Context in SNACS: A 5-Way Classification of Adpositional Pragmatic Markers}},
  booktitle = {Proceedings of The 16th Lingusitic Annotation Workshop (LAW-XVI)},
  year = {2022},
  tags = {Semantics},
  paper = {pdfs/liu2022putting.pdf}
}

@inproceedings{marasovic2022few-shot,
  author = {Marasović, Ana and Beltagy, Iz and Downey, Doug and Peters, Matthew},
  title = {Few-Shot Self-Rationalization with Natural Language Prompts},
  booktitle = {Findings of the Association for Computational Linguistics: NAACL 2022},
  year = {2022},
  tags = {},
  paper = {https://aclanthology.org/2022.findings-naacl.31}
}

@inproceedings{palaskar2022on-advances,
  author = {Palaskar, Shruti and Bhagia, Akshita and Bisk, Yonatan and Metze, Florian and Black, Alan W and Marasović, Ana},
  title = {On Advances in Text Generation from Images Beyond Captioning: A Case Study in Self-Rationalization},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2022},
  year = {2022},
  tags = {},
  paper = {https://arxiv.org/abs/2205.11686}
}

@inproceedings{ross2022does-self-rationalization,
  author = {Ross, Alexis and Peters, Matthew and Marasović, Ana},
  title = {Does Self-Rationalization Improve Robustness to Spurious Correlations?},
  booktitle = {Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing},
  year = {2022},
  tags = {},
  paper = {https://arxiv.org/abs/2210.13575}
}

@inproceedings{ravichander2022condaqa,
  author = {Ravichander, Abhilasha and Gardner, Matt and Marasović, Ana},
  title = {CondaQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation},
  booktitle = {Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing},
  year = {2022},
  tags = {},
  award = {SoCal NLP Symposium Best Paper Award},
  paper = {https://arxiv.org/abs/2211.00295}
}

@inproceedings{zhou2021directprobe,
  author = {Zhou, Yichu and Srikumar, Vivek},
  title = {{DirectProbe: Studying Representations without Classifiers}},
  booktitle = {Proceedings of the 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics},
  year = {2021},
  tags = {Representations & Learning,Probing representations and models},
  paper = {pdfs/zhou2021directprobe.pdf}
}

@inproceedings{wiegreffe2021teach-me,
  author = {Wiegreffe, Sarah and Marasović, Ana},
  title = {Teach Me to Explain: A Review of Datasets for Explainable NLP},
  booktitle = {Proceedings of NeurIPS},
  year = {2021},
  tags = {},
  paper = {https://arxiv.org/abs/2102.12060}
}

@inproceedings{wiegreffe2021measuring,
  author = {Wiegreffe, Sarah and Marasović, Ana and Smith, Noah A.},
  title = {{M}easuring Association Between Labels and Free-Text Rationales},
  booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing},
  year = {2021},
  tags = {},
  paper = {https://aclanthology.org/2021.emnlp-main.804}
}

@article{tanana2021how-do-you,
  author = {Tanana, Michael J. and Soma, Christina S. and Kuo, Patty B. and Bertagnolli, Nicolas M. and Dembe, Aaron and Pace, Brian T. and Srikumar, Vivek and Atkins, David C. and Imel, Zac E.},
  title = {{How Do You Feel? Using Natural Language Processing to Automatically Rate Emotion in Psychotherapy}},
  journal = {Behavior Research Methods},
  year = {2021},
  volume = {53},
  tags = {Clinical Psychology & Technology},
  paper = {pdfs/tanana2021how-do-you.pdf}
}

@inproceedings{sun2021effective,
  author = {Sun, Kaiser and Marasović, Ana},
  title = {Effective Attention Sheds Light On Interpretability},
  booktitle = {Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021},
  year = {2021},
  tags = {},
  paper = {https://aclanthology.org/2021.findings-acl.361}
}

@inproceedings{ross2021explaining,
  author = {Ross, Alexis and Marasović, Ana and Peters, Matthew},
  title = {Explaining {NLP} Models via Minimal Contrastive Editing ({M}i{CE})},
  booktitle = {Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021},
  year = {2021},
  tags = {},
  paper = {https://aclanthology.org/2021.findings-acl.336}
}

@article{prange2021supertagging,
  author = {Prange, Jakob and Schneider, Nathan and Srikumar, Vivek},
  title = {{Supertagging the Long Tail with Tree-Structured Decoding of Complex Categories}},
  journal = {Transactions of the Association for Computational Linguistics},
  year = {2021},
  volume = {9},
  tags = {Structured Learning and Prediction},
  paper = {pdfs/prange2021supertagging.pdf}
}

@inproceedings{neeraja2021incorporating,
  author = {Neeraja, J. and Gupta, Vivek and Srikumar, Vivek},
  title = {{Incorporating External Knowledge to Enhance Tabular Reasoning}},
  booktitle = {Proceedings of the 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics},
  year = {2021},
  tags = {},
  paper = {pdfs/neeraja2021incorporating.pdf}
}

@article{musslick2021sweetpea,
  author = {Musslick, Sebastian and Cherkaev, Anastasia and Draut, Ben and Butt, Ahsan and Darragh, Pierce and Srikumar, Vivek and Flatt, Matthew and Cohen, Jonathan D.},
  title = {{SweetPea: A Standard Language for Factorial Experimental Design}},
  journal = {Behavior Research Methods},
  year = {2021},
  volume = {54},
  tags = {},
  paper = {pdfs/musslick2021sweetpea.pdf}
}

@inproceedings{medina-grespan2021evaluating,
  author = {Medina-Grespan, Mattia and Gupta, Ashim and Srikumar, Vivek},
  title = {{Evaluating Relaxations of Logic for Neural Networks: A Comprehensive Study}},
  booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI)},
  year = {2021},
  tags = {Structured Learning and Prediction},
  paper = {pdfs/medina-grespan2021evaluating.pdf}
}

@inproceedings{kazeminejad2021automatic,
  author = {Kazeminejad, Ghazaleh and Palmer, Martha and Li, Tao and Srikumar, Vivek},
  title = {{Automatic Entity State Annotation using the {V}erb{N}et Semantic Parser}},
  booktitle = {Proceedings of The Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop},
  year = {2021},
  tags = {Semantic Role Labeling,Semantics},
  paper = {pdfs/kazeminejad2021automatic.pdf}
}

@inproceedings{karidi2021putting,
  author = {Karidi, Taelin and Zhou, Yichu and Schneider, Nathan and Abend, Omri and Srikumar, Vivek},
  title = {{Putting Words in BERT's Mouth: Navigating Contextualized Vector Spaces with Pseudowords}},
  booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year = {2021},
  tags = {Representations & Learning,Datasets,Probing representations and models},
  paper = {pdfs/karidi2021putting.pdf}
}

@inproceedings{jiang2021learning,
  author = {Jiang, Tianyu and Riloff, Ellen},
  title = {{Learning Prototypical Functions for Physical Artifacts}},
  booktitle = {Proceedings of the  Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)},
  year = {2021},
  tags = {Common Sense Knowledge},
  paper = {pdfs/jiang2021learning.pdf}
}

@inproceedings{jiang2021exploiting,
  author = {Jiang, Tianyu and Riloff, Ellen},
  title = {{Exploiting Definitions for Frame Identification}},
  booktitle = {Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)},
  year = {2021},
  tags = {Frame Semantics},
  paper = {pdfs/jiang2021exploiting.pdf}
}

@inproceedings{jacovi2021formalizing,
  author = {Jacovi, Alon and Marasović, Ana and Miller, Tim and Goldberg, Yoav},
  title = {Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in {AI}},
  booktitle = {FAccT '21: 2021 {ACM} Conference on Fairness, Accountability, and Transparency, Virtual Event / Toronto, Canada, March 3-10, 2021},
  year = {2021},
  tags = {},
  paper = {https://doi.org/10.1145/3442188.3445923}
}

@inproceedings{hoyle2021promoting,
  author = {Hoyle, Alexander Miserlis and Marasović, Ana and Smith, Noah A.},
  title = {Promoting Graph Awareness in Linearized Graph-to-Text Generation},
  booktitle = {Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021},
  year = {2021},
  tags = {},
  paper = {https://aclanthology.org/2021.findings-acl.82}
}

@inproceedings{gupta2021x-fact,
  author = {Gupta, Ashim and Srikumar, Vivek},
  title = {{X-Fact: A New Benchmark Dataset for Multilingual Fact Checking}},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2021},
  tags = {Datasets},
  paper = {pdfs/gupta2021x-fact.pdf}
}

@inproceedings{gupta2021bert--family,
  author = {Gupta, Ashim and Kvernadze, Giorgi and Srikumar, Vivek},
  title = {{BERT & Family Eat Word Salad: Experiments with Text Understanding}},
  booktitle = {AAAI},
  year = {2021},
  tags = {Representations & Learning},
  paper = {pdfs/gupta2021bert--family.pdf}
}

@inproceedings{dodge2021documenting,
  author = {Dodge, Jesse and Sap, Maarten and Marasović, Ana and Agnew, William and Ilharco, Gabriel and Groeneveld, Dirk and Mitchell, Margaret and Gardner, Matt},
  title = {Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus},
  booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing},
  year = {2021},
  tags = {},
  paper = {https://aclanthology.org/2021.emnlp-main.98}
}

@inproceedings{dev2021oscar,
  author = {Dev, Sunipa and Li, Tao and Phillips, Jeff and Srikumar, Vivek},
  title = {{OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings}},
  booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year = {2021},
  tags = {Representations & Learning,Fairness},
  paper = {pdfs/dev2021oscar.pdf}
}

@inproceedings{zhuang2020exploring,
  author = {Zhuang, Yuan and Riloff, Ellen},
  title = {{  Exploring the Role of Context to Distinguish Rhetorical and Information-Seeking Questions}},
  booktitle = {The ACL 2020 Student Research Workshop (SRW)},
  year = {2020},
  tags = {Discourse,Pragmatics},
  paper = {pdfs/zhuang2020exploring.pdf}
}

@inproceedings{zhuang2020affective,
  author = {Zhuang, Yuan and Jiang, Tianyu and Riloff, Ellen},
  title = {{Affective Event Classification with Discourse-enhanced Self-training}},
  booktitle = {The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)},
  year = {2020},
  tags = {Sentiment,Events},
  paper = {pdfs/zhuang2020affective.pdf}
}

@unpublished{zhou2020simple,
  author = {Zhou, Yichu and Koshorek, Omri and Srikumar, Vivek and Berant, Jonathan},
  title = {{A Simple Global Neural Discourse Parser}},
  note = {arXiv preprint arXiv:2009.01312},
  year = {2020},
  tags = {Structured Learning and Prediction},
  paper = {pdfs/zhou2020simple.pdf}
}

@article{schroeder2020prediction,
  author = {Schroeder, Joyce D and Lanfredi, Ricardo Bigolin and Li, Tao and Chan, Jessica and Vachet, Clement and Paine III, Robert and Srikumar, Vivek and Tasdizen, Tolga},
  title = {{Prediction of Obstructive Lung Disease from Chest Radiographs via Deep Learning Trained on Pulmonary Function Data}},
  journal = {International Journal of Chronic Obstructive Pulmonary Disease},
  year = {2020},
  volume = {15},
  tags = {Deep Learning},
  paper = {pdfs/schroeder2020prediction.pdf}
}

@inproceedings{pan2020learning,
  author = {Pan, Xingyuan and Mehta, Maitrey and Srikumar, Vivek},
  title = {{Learning Constraints for Structured Prediction Using Rectifier Networks}},
  booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
  year = {2020},
  tags = {Deep Learning,Representations & Learning,Structured Learning and Prediction},
  paper = {pdfs/pan2020learning.pdf}
}

@inproceedings{ning2020easy-reproducible,
  author = {Ning, Qiang and Wu, Hao and Dasigi, Pradeep and Dua, Dheeru and Gardner, Matt and Logan IV, Robert L. and Marasović, Ana and Nie, Zhen},
  title = {Easy, Reproducible and Quality-Controlled Data Collection with {CROWDAQ}},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  year = {2020},
  tags = {},
  paper = {https://aclanthology.org/2020.emnlp-demos.17}
}

@inproceedings{marasovic2020natural,
  author = {Marasović, Ana and Bhagavatula, Chandra and Park, Jae sung and Le Bras, Ronan and Smith, Noah A. and Choi, Yejin},
  title = {Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2020},
  year = {2020},
  tags = {},
  paper = {https://aclanthology.org/2020.findings-emnlp.253}
}

@inproceedings{li2020unqovering,
  author = {Li, Tao and Khot, Tushar and Khashabi, Daniel and Sabarwal, Ashish and Srikumar, Vivek},
  title = {{UNQOVERing Stereotyping Biases via Underspecified Questions}},
  booktitle = {Findings of EMNLP},
  year = {2020},
  tags = {Representations & Learning},
  paper = {pdfs/li2020unqovering.pdf}
}

@inproceedings{li2020structured,
  author = {Li, Tao and Jawale, Parth Anand and Palmer, Martha and Srikumar, Vivek},
  title = {{Structured Tuning for Semantic Role Labeling}},
  booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
  year = {2020},
  tags = {Semantic Role Labeling,Frame Semantics,Deep Learning,Structured Learning and Prediction},
  paper = {pdfs/li2020structured.pdf}
}

@inproceedings{hwang2020sprucing,
  author = {Hwang, Jena D. and Schneider, Nathan and Srikumar, Vivek},
  title = {Sprucing up Supersenses: Untangling the Semantic Clusters of Accompaniment and Purpose},
  booktitle = {Proceedings of the 14th Linguistic Annotation Workshop},
  year = {2020},
  tags = {Preposition Semantics},
  paper = {pdfs/hwang2020sprucing.pdf}
}

@inproceedings{gururangan2020dont-stop,
  author = {Gururangan, Suchin and Marasović, Ana and Swayamdipta, Swabha and Lo, Kyle and Beltagy, Iz and Downey, Doug and Smith, Noah A.},
  title = {Don{'}t Stop Pretraining: Adapt Language Models to Domains and Tasks},
  booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
  year = {2020},
  tags = {},
  paper = {https://aclanthology.org/2020.acl-main.740},
  award = {Honorable Mention for ACL 2020 Best Paper Award}
}

@inproceedings{gupta2020infotabs,
  author = {Gupta, Vivek and Nokhiz, Pegah and Mehta, Maitrey and Srikumar, Vivek},
  title = {{InfoTabS: Inference on Tables as Semi-structured Data}},
  booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
  year = {2020},
  tags = {Textual entailment,Datasets},
  paper = {pdfs/gupta2020infotabs.pdf}
}

@inproceedings{felt2020recognizing,
  author = {Felt, Christian and Riloff, Ellen},
  title = {{Recognizing Euphemisms and Dysphemisms Using Sentiment Analysis}},
  booktitle = {The Second Workshop on Figurative Language Processing (FigLang2020)},
  year = {2020},
  tags = {Sentiment},
  paper = {pdfs/felt2020recognizing.pdf}
}

@inproceedings{dev2020on-measuring,
  author = {Dev, Sunipa and Li, Tao and Phillips, Jeff and Srikumar, Vivek},
  title = {{On Measuring and Mitigating Biased Inferences of Word Embeddings}},
  booktitle = {AAAI},
  year = {2020},
  tags = {Representations & Learning,Fairness},
  paper = {pdfs/dev2020on-measuring.pdf}
}

@inproceedings{zhou2019beyond,
  author = {Zhou, Yichu and Srikumar, Vivek},
  title = {{Beyond Context: A New Perspective for Word Embeddings}},
  booktitle = {*SEM},
  year = {2019},
  tags = {Representations & Learning},
  paper = {pdfs/zhou2019beyond.pdf}
}

@article{tanana2019development,
  author = {Tanana, Michael J. and Soma, Christina S. and Srikumar, Vivek and Atkins, David C. and Imel, Zac E.},
  title = {{Development and evaluation of ClientBot: A patient-like conversational agent to train basic counseling skills}},
  journal = {Journal of Medical Internet Research},
  year = {2019},
  volume = {21},
  tags = {Clinical Psychology & Technology},
  paper = {pdfs/tanana2019development.pdf}
}

@inproceedings{shalev2019preparing,
  author = {Shalev, Adi and Hwang, Jena D. and Schneider, Nathan and Srikumar, Vivek and Abend, Omri and Rappoport, Ari},
  title = {{Preparing SNACS for Subjects and Objects}},
  booktitle = {The First International Workshop on Designing Meaning Representations (DMR)},
  year = {2019},
  tags = {Preposition Semantics,Semantic Role Labeling,Frame Semantics},
  paper = {pdfs/shalev2019preparing.pdf}
}

@article{liu2019nlize,
  author = {Liu, Shusen and Li, Zhimin and Li, Tao and Srikumar, Vivek and Pascucci, Valerio and Bremer, Peer-Timo},
  title = {{NLIZE: A Perturbation-Driven Visual Interrogation Tool for Analyzing and Interpreting Natural Language Inference Models}},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  year = {2019},
  volume = {25},
  tags = {Neural Networks,Text Understanding,Visualizing NLP,Software and Tools},
  paper = {pdfs/liu2019nlize.pdf}
}

@inproceedings{li2019logic-driven,
  author = {Li, Tao and Gupta, Vivek and Mehta, Maitrey and Srikumar, Vivek},
  title = {{A Logic-Driven Framework for Consistency of Neural Models}},
  booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year = {2019},
  tags = {Deep Learning,Structured Learning and Prediction,Representations & Learning},
  paper = {pdfs/li2019logic-driven.pdf}
}

@inproceedings{li2019augmenting,
  author = {Li, Tao and Srikumar, Vivek},
  title = {{Augmenting Neural Networks with First-order Logic}},
  booktitle = {Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2019},
  tags = {Representations & Learning,Textual entailment,Deep Learning},
  paper = {pdfs/li2019augmenting.pdf}
}

@inproceedings{koshorek2019on-the-limits,
  author = {Koshorek, Omri and Stanovsky, Gabriel and Zhou, Yichu and Srikumar, Vivek and Berant, Jonathan},
  title = {{On the Limits of Learning to Actively Learn Semantic Representations}},
  booktitle = {Proceedings of the Conference on Natural Language Learning (CoNLL)},
  year = {2019},
  tags = {Semantic Role Labeling,Frame Semantics,Representations & Learning},
  paper = {pdfs/koshorek2019on-the-limits.pdf},
  award = {Best paper honorable mention}
}

@inproceedings{ding2019improving,
  author = {Ding, Haibo and Riloff, Ellen and Feng, Zhe},
  title = {{Improving Human Needs Categorization of Events with Semantic Classification}},
  booktitle = { Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)  },
  year = {2019},
  tags = {Sentiment,Events},
  paper = {pdfs/ding2019improving.pdf}
}

@inproceedings{dasigi2019quoref,
  author = {Dasigi, Pradeep and Liu, Nelson F. and Marasović, Ana and Smith, Noah A. and Gardner, Matt},
  title = {{Q}uoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning},
  booktitle = {Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
  year = {2019},
  tags = {},
  paper = {https://aclanthology.org/D19-1606}
}

@unpublished{cherkaev2019learning,
  author = {Cherkaev, Annie and Tai, Waiming and Phillips, Jeff and Srikumar, Vivek},
  title = {{Learning In Practice: Reasoning About Quantization}},
  note = {arXiv preprint arXiv:1905.11478},
  year = {2019},
  tags = {ML & Systems,Representations & Learning},
  paper = {pdfs/cherkaev2019learning.pdf}
}

@inproceedings{cao2019observing,
  author = {Cao, Jie and Tanana, Michael and Imel, Zac and Poitras, Eric and Atkins, David and Srikumar, Vivek},
  title = {{Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes}},
  booktitle = {Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2019},
  tags = {Clinical Psychology & Technology,Applied ML,Deep Learning},
  paper = {pdfs/cao2019observing.pdf}
}

@inproceedings{zopf2018whats,
  author = {Zopf, Markus and Botschen, Teresa and Falke, Tobias and Heinzerling, Benjamin and Marasović, Ana and Mihaylov, Todor and S., Avinesh P. V. and Mencía, Eneldo Loza and Fürnkranz, Johannes and Frank, Anette},
  title = {What's Important in a Text? An Extensive Evaluation of Linguistic Annotations for Summarization},
  booktitle = {Fifth International Conference on Social Networks Analysis, Management and Security, {SNAMS} 2018, Valencia, Spain, October 15-18, 2018},
  year = {2018},
  tags = {},
  paper = {https://doi.org/10.1109/SNAMS.2018.8554853}
}

@inproceedings{wagstaff2018mars-target,
  author = {Wagstaff, Kiri and Francis, Raymond and Gowda, Thamme and Lu, You and Riloff, Ellen and Singh, Karanjeet and Lanza, Nina},
  title = {{Mars Target Encyclopedia: Rock and Soil Composition Extracted from the Literature  }},
  booktitle = { Proceedings of the Thirtieth Conference on Innovative Applications of Artificial Intelligence (IAAI-18)},
  year = {2018},
  tags = {Information Extraction,Planetary Science},
  paper = {pdfs/wagstaff2018mars-target.pdf}
}

@inproceedings{schneider2018comprehensive,
  author = {Schneider, Nathan and Hwang, Jena D. and Srikumar, Vivek and Prange, Jakob and Blodgett, Austin and Moeller, Sarah and Stern, Aviram and Bitan, Adi and Abend, Omri},
  title = {Comprehensive supersense disambiguation of {E}nglish prepositions and possessives},
  booktitle = {Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2018},
  tags = {Preposition Semantics},
  paper = {pdfs/schneider2018comprehensive.pdf}
}

@article{riloff2018retrospective,
  author = {Riloff, Ellen and Jones, Rosie},
  title = {{A Retrospective on Mutual Bootstrapping}},
  journal = {AI Magazine},
  year = {2018},
  volume = {39},
  tags = {Information Extraction},
  paper = {https://www.aaai.org/ojs/index.php/aimagazine/article/view/2778}
}

@article{rahman2018predicting,
  author = {Rahman, Aowabin and Srikumar, Vivek and Smith, Amanda D.},
  title = {Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks},
  journal = {Applied Energy},
  year = {2018},
  volume = {212},
  tags = {Applied ML,Neural Networks},
  paper = {pdfs/rahman2018predicting.pdf}
}

@inproceedings{pan2018learning,
  author = {Pan, Xingyuan and Srikumar, Vivek},
  title = {Learning to Speed Up Structured Output Prediction},
  booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
  year = {2018},
  tags = {Efficient machine learning,Structured Learning and Prediction},
  paper = {pdfs/pan2018learning.pdf}
}

@article{nag2018newton,
  author = {Nag, Anirban and Shafiee, Ali and Balasubramonian, Rajeev and Srikumar, Vivek and Walker, Ross and Strachan, John Paul and Muralimanohar, Naveen},
  title = {{Newton: Gravitating Towards the Physical Limits of Crossbar Acceleration}},
  journal = {IEEE Micro},
  year = {2018},
  volume = {38},
  tags = {Neural Networks,ML & Systems,Efficient machine learning},
  paper = {pdfs/nag2018newton.pdf}
}

@inproceedings{marasovic2018srl4orl,
  author = {Marasović, Ana and Frank, Anette},
  title = {{SRL}4{ORL}: Improving Opinion Role Labeling Using Multi-Task Learning with Semantic Role Labeling},
  booktitle = {Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)},
  year = {2018},
  tags = {},
  paper = {https://aclanthology.org/N18-1054}
}

@article{liu2018visuala,
  author = {Liu, Shusen and Bremer, Peer-Timo and Thiagarajan, Jayaraman J. and Srikumar, Vivek and Wang, Bei and Livnat, Yarden and Pascucci, Valerio},
  title = {{Visual Exploration of Semantic Relationships in Neural Word Embeddings}},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  year = {2018},
  volume = {24},
  tags = {Representations & Learning,Visualizing NLP,Neural Networks,Software and Tools},
  paper = {pdfs/liu2018visuala.pdf}
}

@inproceedings{liu2018visual,
  author = {Liu, Shusen and Li, Tao and Li, Zhimin and Srikumar, Vivek and Pascucci, Valerio and Bremer, Peer-Timo},
  title = {{Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension}},
  booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP): System Demonstrations},
  year = {2018},
  tags = {Textual entailment,Neural Networks,Software and Tools,Visualizing NLP},
  paper = {pdfs/liu2018visual.pdf}
}

@inproceedings{khashabi2018cogcompnlp,
  author = {Khashabi, Daniel and Sammons, Mark and Zhou, Ben and Redman, Tom and Christodoulopoulos, Christos and Srikumar, Vivek and Rizzolo, Nicholas and Ratinov, Lev and Luo, Guanheng and Do, Quang and Tsai, Chen-Tse and Roy, Subhro and Mayhew, Stephen and Feng, Zhili and Wieting, John and Yu, Xiaodong and Song, Yangqiu and Gupta, Shashank and Upadhyay, Shyam and Arivazhagan, Naveen and Ning, Qiang and Ling, Shaoshi and Roth, Dan},
  title = {{CogCompNLP: Your Swiss Army Knife for NLP}},
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC)},
  year = {2018},
  tags = {Software and Tools},
  paper = {pdfs/khashabi2018cogcompnlp.pdf}
}

@inproceedings{jiang2018learning,
  author = {Jiang, Tianyu and Riloff, Ellen},
  title = {{Learning Prototypical Goal Activities for Locations}},
  booktitle = { Proceedings of the 56th Annual Meeting of the Association for Computationnal Linguistics(ACL 2018)},
  year = {2018},
  tags = {Common Sense Knowledge},
  paper = {pdfs/jiang2018learning.pdf}
}

@inproceedings{ding2018why-is-an,
  author = {Ding, Haibo and Jiang, Tianyu and Riloff, Ellen},
  title = {{Why is an Event Affective? Classifying Affective Events based on Human Needs  }},
  booktitle = {AAAI-18 Workshop on Affective Content Analysis},
  year = {2018},
  tags = {Sentiment,Events},
  paper = {pdfs/ding2018why-is-an.pdf}
}

@inproceedings{ding2018weakly,
  author = {Ding, Haibo and Riloff, Ellen},
  title = {{Weakly Supervised Induction of Affective Events by Optimizing Semantic Consistency}},
  booktitle = {Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)},
  year = {2018},
  tags = {Sentiment,Events},
  paper = {pdfs/ding2018weakly.pdf}
}

@inproceedings{ding2018human-needs,
  author = {Ding, Haibo and Riloff, Ellen},
  title = {{Human Needs Categorization of Affective Events Using Labeled and Unlabeled Data}},
  booktitle = { Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2018)},
  year = {2018},
  tags = {Sentiment,Events},
  paper = {pdfs/ding2018human-needs.pdf}
}

@inproceedings{wagstaff2017mars-target,
  author = {Wagstaff, Kiri and Francis, Raymond and Gowda, Thamme and Lu, You and Riloff, Ellen and Singh, Karanjeet},
  title = {{Mars Target Encyclopedia: Information Extraction for Planetary Science }},
  booktitle = {Third Planetary Data Workshop 2017},
  year = {2017},
  tags = {Information Extraction,Planetary Science},
  paper = {pdfs/wagstaff2017mars-target.pdf}
}

@inproceedings{srikumar2017algebra,
  author = {Srikumar, Vivek},
  title = {{An Algebra for Feature Extraction}},
  booktitle = {Annual meeting of the Association of Computational Linguistics (ACL)},
  year = {2017},
  tags = {Representations & Learning,Efficient machine learning},
  paper = {pdfs/srikumar2017algebra.pdf}
}

@unpublished{schneider2017adposition,
  author = {Schneider, Nathan and Hwang, Jena D. and Bhatia, Archna and Han, Na-Rae and Srikumar, Vivek and O'Gorman, Tim and Abend, Omri},
  title = {{Adposition Supersenses v2}},
  note = {arXiv preprint arXiv:1704.02134},
  year = {2017},
  tags = {Preposition Semantics,Semantic Role Labeling,Frame Semantics,Datasets},
  paper = {pdfs/schneider2017adposition.pdf}
}

@inproceedings{roth2017integer,
  author = {Roth, Dan and Srikumar, Vivek},
  title = {{Integer Linear Programming Formulations in Natural Language Processing}},
  booktitle = {EACL},
  year = {2017},
  tags = {Tutorial,Structured Learning and Prediction,Integer linear programming},
  paper = {pdfs/roth2017integer.pdf}
}

@inproceedings{oraby2017are-you,
  author = {Oraby, Shereen and Harrison, Vrindavan and Misra, Amita and Riloff, Ellen and Walker, Marilyn},
  title = {{Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog}},
  booktitle = {Proceedings of the 18th Annual SIGdial Meeting on  Discourse and Dialogue (SIGDIAL 2017)},
  year = {2017},
  tags = {Sarcasm},
  paper = {pdfs/oraby2017are-you.pdf}
}

@inproceedings{marasovic2017mention-ranking,
  author = {Marasović, Ana and Born, Leo and Opitz, Juri and Frank, Anette},
  title = {A Mention-Ranking Model for Abstract Anaphora Resolution},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  year = {2017},
  tags = {},
  paper = {https://aclanthology.org/D17-1021}
}

@inproceedings{kim2017exploiting,
  author = {Kim, Youngjun and Riloff, Ellen and Meystre, Stéphane},
  title = {{Exploiting Unlabeled Texts with Clustering-based Instance Selection for Medical Relation Classification}},
  booktitle = {Proceedings of the AMIA 2017 Annual Symposium (AMIA 2017)},
  year = {2017},
  tags = {Information Extraction,Medicine},
  paper = {pdfs/kim2017exploiting.pdf},
  award = {Finalist for AMIA 2017 Distinguished Paper Award}
}

@inproceedings{hwang2017double,
  author = {Hwang, Jena D. and Bhatia, Archna and Han, Na-Rae and O'Gorman, Tim and Srikumar, Vivek and Schneider, Nathan},
  title = {{Double Trouble: The Problem of Construal in Semantic Annotation of Adpositions}},
  booktitle = {*SEM},
  year = {2017},
  tags = {Preposition Semantics,Semantic Role Labeling,Frame Semantics},
  paper = {pdfs/hwang2017double.pdf}
}

@inproceedings{hwang2017coping,
  author = {Hwang, Jena D. and Bhatia, Archna and Han, Na-Rae and O'Gorman, Tim and Srikumar, Vivek and Schneider, Nathan},
  title = {{Coping with Construals in Broad-Coverage Semantic Annotation of Adpositions}},
  booktitle = {AAAI Spring Symposium on Computational Construction Grammar and Natural Language Understanding},
  year = {2017},
  tags = {Preposition Semantics,Semantic Role Labeling,Frame Semantics},
  paper = {pdfs/hwang2017coping.pdf}
}

@inproceedings{du2017deeplog,
  author = {Du, Min and Li, Feifei and Zheng, Guineng and Srikumar, Vivek},
  title = {{DeepLog: Anomaly Detection and Diagnosis from System Logs through Deep Learning}},
  booktitle = {Proceedings of 24th ACM Conference on Computer and Communications Security},
  year = {2017},
  tags = {Applied ML,Neural Networks},
  paper = {pdfs/du2017deeplog.pdf}
}

@inproceedings{wagstaff2016creating,
  author = {Wagstaff, Kiri and Riloff, Ellen and Lanza, Nina and Mattmann, Chris and Ramirez, Paul},
  title = {{Creating a Mars Target Encyclopedia by Extracting Information from the Planetary Science Literature}},
  booktitle = { AAAI-16 Workshop on Knowledge Extraction from Text (KET).},
  year = {2016},
  tags = {Information Extraction,Planetary Science},
  paper = {pdfs/wagstaff2016creating.pdf}
}

@inproceedings{tanana2016is-sentiment,
  author = {Tanana, Michael and Dembe, Aaron and Soma, Christina S. and Atkins, David C. and Imel, Zac and Srikumar, Vivek},
  title = {{Is Sentiment in Movies the Same as Sentiment in Psychotherapy? Comparisons Using a New Psychotherapy Sentiment Database}},
  booktitle = {Proceedings of the 3nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality},
  year = {2016},
  tags = {Clinical Psychology & Technology,Neural Networks,Applied ML},
  paper = {pdfs/tanana2016is-sentiment.pdf}
}

@article{tanana2016comparison,
  author = {Tanana, Michael and Hallgren, Kevin A. and Imel, Zac E. and Atkins, David C. and Srikumar, Vivek},
  title = {{A Comparison of Natural Language Processing Methods for Automated Coding of Motivational Interviewing}},
  journal = {Journal of Substance Abuse Treatment},
  year = {2016},
  volume = {65},
  tags = {Applied ML,Clinical Psychology & Technology,Neural Networks},
  paper = {pdfs/tanana2016comparison.pdf}
}

@inproceedings{shafiee2016isaac,
  author = {Shafiee, Ali and Nag, Anirban and Muralimanohar, Naveen and Balasubramonian, Rajeev and Strachan, John Paul and Hu, Miao and Williams, R. Stanley and Srikumar, Vivek},
  title = {{ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars}},
  booktitle = {ISCA},
  year = {2016},
  tags = {Neural Networks,ML & Systems,Efficient machine learning},
  paper = {pdfs/shafiee2016isaac.pdf},
  award = {IEEE Micro top picks of the year, honorable mention}
}

@inproceedings{schneider2016corpus,
  author = {Schneider, Nathan and Hwang, Jena D. and Srikumar, Vivek and Suresh, Abhijit and Green, Meredith and Conger, Kathryn and O'Gorman, Tim and Palmer, Martha},
  title = {{A corpus of preposition supersenses in English web reviews}},
  booktitle = {Linguistic Annotation Workshop},
  year = {2016},
  tags = {Preposition Semantics,Semantic Role Labeling,Frame Semantics,Datasets},
  paper = {pdfs/schneider2016corpus.pdf}
}

@inproceedings{sammons2016edison,
  author = {Sammons, Mark and Christodoulopoulos, Christos and Kordjamshidi, Parisa and Khashabi, Daniel and Srikumar, Vivek and Vijayakumar, Paul and Bokhari, Mazin and Wu, Xinbo and Roth, Dan},
  title = {{EDISON: Feature Extraction for NLP, Simplified}},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
  year = {2016},
  tags = {Software and Tools},
  paper = {pdfs/sammons2016edison.pdf}
}

@inproceedings{qadir2016automatically,
  author = {Qadir, Ashequl and Riloff, Ellen and Walker, Marilyn},
  title = {{Automatically Inferring Implicit Properties in Similes}},
  booktitle = {Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2016)},
  year = {2016},
  tags = {Similes},
  paper = {https://aclanthology.org/N16-1146/}
}

@inproceedings{pan2016expressiveness,
  author = {Pan, Xingyuan and Srikumar, Vivek},
  title = {Expressiveness of Rectifier Networks},
  booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
  year = {2016},
  tags = {Neural Networks,Representations & Learning},
  paper = {pdfs/pan2016expressiveness.pdf}
}

@inproceedings{oraby2016creating,
  author = {Oraby, Shereen and Harrison, Vrindavan and Reed, Lena and Hernandez, Ernesto and Riloff, Ellen and Walker, Marilyn},
  title = {{Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue}},
  booktitle = { Proceedings of the 17th Annual SIGdial Meeting on  Discourse and Dialogue (SIGDIAL 2016)},
  year = {2016},
  tags = {Sarcasm},
  paper = {pdfs/oraby2016creating.pdf}
}

@inproceedings{moeller2016continuous,
  author = {Moeller, John and Srikumar, Vivek and Swaminathan, Sarathkrishna and Venkatasubramanian, Suresh and Webb, Dustin},
  title = {{Continuous Kernel Learning}},
  booktitle = {European Conference on Machine Learning (ECML)},
  year = {2016},
  tags = {Neural Networks,Representations & Learning},
  paper = {pdfs/moeller2016continuous.pdf}
}

@inproceedings{marasovic2016multilingual,
  author = {Marasović, Ana and Frank, Anette},
  title = {Multilingual Modal Sense Classification using a Convolutional Neural Network},
  booktitle = {Proceedings of the 1st Workshop on Representation Learning for {NLP}},
  year = {2016},
  tags = {},
  paper = {https://aclanthology.org/W16-1613}
}

@inproceedings{marasovic2016modal-sense,
  author = {Marasović, Ana and Zhou, Mengfei and Palmer, Alexis and Frank, Anette},
  title = {Modal Sense Classification At Large: Paraphrase-Driven Sense Projection, Semantically Enriched Classification Models and Cross-Genre Evaluations},
  booktitle = {Linguistic Issues in Language Technology, Volume 14, 2016 - Modality: Logic, Semantics, Annotation, and Machine Learning},
  year = {2016},
  tags = {},
  paper = {https://aclanthology.org/2016.lilt-14.3}
}

@inproceedings{li2016exploiting,
  author = {Li, Tao and Srikumar, Vivek},
  title = {{Exploiting Sentence Similarities for Better Alignments}},
  booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year = {2016},
  tags = {Integer linear programming,Structured Learning and Prediction,Textual entailment},
  paper = {pdfs/li2016exploiting.pdf}
}

@inproceedings{kumar2016unsupervised,
  author = {Kumar, Shachi and Pujara, Jay and Getoor, Lise and Mares, David and Gupta, Dipak and Riloff, Ellen},
  title = {{Unsupervised Models for Predicting Strategic Relations between Organizations}},
  booktitle = {The 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016)},
  year = {2016},
  tags = {Social Media},
  paper = {pdfs/kumar2016unsupervised.pdf}
}

@inproceedings{huang2016distinguishing,
  author = {Huang, Ruihong and Cases, Ignacio and Jurafsky, Dan and Condoravdi, Cleo and Riloff, Ellen},
  title = {{Distinguishing Past, On-going, and Future Events: The EventStatus Corpus}},
  booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP 2016)},
  year = {2016},
  tags = {Events,Temporal},
  paper = {pdfs/huang2016distinguishing.pdf}
}

@inproceedings{ding2016acquiring,
  author = {Ding, Haibo and Riloff, Ellen},
  title = {{Acquiring Knowledge of Affective Events from Blogs using Label Propagation}},
  booktitle = {Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016)},
  year = {2016},
  tags = {Sentiment,Events},
  paper = {pdfs/ding2016acquiring.pdf}
}

@inproceedings{chang2016learning,
  author = {Chang, Kai-Wei and Kundu, Gourab and Roth, Dan and Srikumar, Vivek},
  title = {{Learning and Inference in Structured Prediction Models}},
  booktitle = {AAAI-16 Tutorial Forum},
  year = {2016},
  tags = {Tutorial,Structured Learning and Prediction},
  paper = {pdfs/chang2016learning.pdf}
}

@inproceedings{tanana2015recursive,
  author = {Tanana, Michael and Hallgren, Kevin and Imel, Zac and Atkins, David and Smyth, Padhraic and Srikumar, Vivek},
  title = {{Recursive Neural Networks for Coding Therapist and Patient Behavior in Motivational Interviewing}},
  booktitle = {Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality},
  year = {2015},
  tags = {Clinical Psychology & Technology,Neural Networks,Applied ML},
  paper = {pdfs/tanana2015recursive.pdf}
}

@inproceedings{schneider2015hierarchy,
  author = {Schneider, Nathan and Srikumar, Vivek and Hwang, Jena D. and Palmer, Martha},
  title = {{A Hierarchy with, of, and for Preposition Supersenses}},
  booktitle = {Linguistic Annotation Workshop},
  year = {2015},
  tags = {Preposition Semantics,Semantic Role Labeling,Frame Semantics,Datasets},
  paper = {pdfs/schneider2015hierarchy.pdf}
}

@inproceedings{qadir2015learning,
  author = {Qadir, Ashequl and Riloff, Ellen and Walker, Marilyn},
  title = {{Learning to Recognize Affective Polarity in Similes}},
  booktitle = {Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP 2015)},
  year = {2015},
  tags = {Similes,Sentiment},
  paper = {https://aclanthology.org/D15-1019/}
}

@inproceedings{oraby2015and-thats,
  author = {Oraby, Shereen and Reed, Lena and Compton, Ryan and Riloff, Ellen and Walker, Marilyn and Whittaker, Steve},
  title = {{And That's a Fact: Distinguishing Factual and Emotional Argumentation in Online Dialogue}},
  booktitle = { 2nd Workshop on Argumentation Mining at NAACL 2015},
  year = {2015},
  tags = {Sentiment,Argumentation},
  paper = {pdfs/oraby2015and-thats.pdf}
}

@inproceedings{mccurdy2015rhymedesign,
  author = {McCurdy, Nina and Srikumar, Vivek and Meyer, Miriah},
  title = {{RhymeDesign: A Tool for Analyzing Sonic Devices in Poetry}},
  booktitle = {Proceedings of the Fourth Workshop on Computational Linguistics for Literature},
  year = {2015},
  tags = {Applied ML},
  paper = {pdfs/mccurdy2015rhymedesign.pdf}
}

@inproceedings{kim2015study-of,
  author = {Kim, Youngjun and Riloff, Ellen and Hurdle, John},
  title = {{A Study of Concept Extraction Across Different Types of Clinical Notes}},
  booktitle = { Proceedings of the AMIA 2015 Annual Symposium (AMIA 2015)},
  year = {2015},
  tags = {Information Extraction,Medicine},
  paper = {pdfs/kim2015study-of.pdf}
}

@inproceedings{kim2015stacked,
  author = {Kim, Youngjun and Riloff, Ellen},
  title = {{Stacked Generalization for Medical Concept Extraction from Clinical Notes}},
  booktitle = {ACL 2015 Workshop on Biomedical Natural Language Processing (BioNLP 2015)},
  year = {2015},
  tags = {Information Extraction,Medicine},
  paper = {pdfs/kim2015stacked.pdf}
}

@inproceedings{ding2015extracting,
  author = {Ding, Haibo and Riloff, Ellen},
  title = {{Extracting Information about Medication Use from Veterinary Discussions}},
  booktitle = {  Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL 2015)},
  year = {2015},
  tags = {Information Extraction,Veternary},
  paper = {pdfs/ding2015extracting.pdf}
}

@inproceedings{srikumar2014learning,
  author = {Srikumar, Vivek and Manning, Christopher D.},
  title = {{Learning Distributed Representations for Structured Output Prediction}},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2014},
  tags = {Representations & Learning,Structured Learning and Prediction},
  paper = {pdfs/srikumar2014learning.pdf},
  award = {Spotlight presentation}
}

@inproceedings{rozovskaya2014correcting,
  author = {Rozovskaya, Alla and Roth, Dan and Srikumar, Vivek},
  title = {{Correcting Grammatical Verb Errors}},
  booktitle = {Conference of the European Chapter of the ACL (EACL)},
  year = {2014},
  tags = {Applied ML},
  paper = {pdfs/rozovskaya2014correcting.pdf}
}

@inproceedings{riedel2014wolfe,
  author = {Riedel, Sebastian and Singh, Sameer and Srikumar, Vivek and Rocktaschel, Tim and Visengeriyeva, Larysa and Noessner, Jan},
  title = {{WOLFE: Strength Reduction and Approximate Programming for Probabilistic Programming}},
  booktitle = {International Workshop on Statistical Relational AI (StarAI)},
  year = {2014},
  tags = {Software and Tools},
  paper = {pdfs/riedel2014wolfe.pdf}
}

@inproceedings{qadir2014learning,
  author = {Qadir, Ashequl and Riloff, Ellen},
  title = {{Learning Emotion Indicators from Tweets: Hashtags, Hashtag Patterns, and Phrases}},
  booktitle = {2014 Conference on Empirical Methods in Natural Language Processing (EMNLP 2014)},
  year = {2014},
  tags = {Sentiment,Social Media},
  paper = {pdfs/qadir2014learning.pdf}
}

@inproceedings{desilva2014user-type,
  author = {De Silva, Lalindra and Riloff, Ellen},
  title = {{User Type Classification of Tweets with Implications for Event Recognition}},
  booktitle = {2014 ACL Joint Workshop on Social Dynamics and Personal Attributes in Social Media},
  year = {2014},
  tags = {Social Media,Events},
  paper = {pdfs/desilva2014user-type.pdf}
}

@inproceedings{berant2014modeling,
  author = {Berant, Jonathan and Srikumar, Vivek and Chen, Pei-Chun and Vander Linden, Abby and Harding, Brittany and Huang, Brad and Clark, Peter and Manning, Christopher D.},
  title = {{Modeling Biological Processes for Reading Comprehension}},
  booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year = {2014},
  tags = {Integer linear programming,Datasets},
  paper = {pdfs/berant2014modeling.pdf},
  award = {Best paper award}
}

@unpublished{srikumar2013soft-constraints,
  author = {Srikumar, Vivek},
  title = {{Soft Constraints in Integer Linear Programs}},
  note = {Unpublished note},
  year = {2013},
  tags = {Tutorial,Inference,Integer linear programming},
  paper = {pdfs/srikumar2013soft-constraints.pdf}
}

@phdthesis{srikumar2013semantics,
  author = {Srikumar, Vivek},
  title = {{The Semantics of Role Labeling}},
  school = {University of Illinois at Urbana-Champaign},
  year = {2013},
  tags = {Semantic Role Labeling,Frame Semantics,Preposition Semantics,Integer linear programming,Datasets,Representations & Learning,Inference},
  paper = {pdfs/srikumar2013semantics.pdf}
}

@article{srikumar2013modeling,
  author = {Srikumar, Vivek and Roth, Dan},
  title = {{Modeling Semantic Relations Expressed by Prepositions}},
  journal = {Transactions of the Association for Computational Linguistics (TACL)},
  year = {2013},
  volume = {1},
  tags = {Datasets,Preposition Semantics,Semantic Role Labeling,Frame Semantics,Structured Learning and Prediction},
  paper = {pdfs/srikumar2013modeling.pdf}
}

@unpublished{srikumar2013inventory,
  author = {Srikumar, Vivek and Roth, Dan},
  title = {{An Inventory of Preposition Relations}},
  note = {arXiv preprint arXiv:1305.5785},
  year = {2013},
  tags = {Preposition Semantics,Semantic Role Labeling,Frame Semantics,Datasets},
  paper = {pdfs/srikumar2013inventory.pdf}
}

@inproceedings{riloff2013sarcasm,
  author = {Riloff, Ellen and Qadir, Ashequl and Surve, Prafulla and De Silva, Lalindra and Gilbert, Nathan and Huang, Ruihong},
  title = {{Sarcasm as Contrast between a Positive Sentiment and Negative Situation}},
  booktitle = { Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013)},
  year = {2013},
  tags = {Sarcasm,Sentiment},
  paper = {pdfs/riloff2013sarcasm.pdf}
}

@inproceedings{qadir2013bootstrapped,
  author = {Qadir, Ashequl and Riloff, Ellen},
  title = {{Bootstrapped Learning of Emotion  Hashtags #hashtags4you}},
  booktitle = {The 4th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA 2013)},
  year = {2013},
  tags = {Sentiment,Social Media},
  paper = {pdfs/qadir2013bootstrapped.pdf}
}

@inproceedings{kundu2013margin-based,
  author = {Kundu, Gourab and Srikumar, Vivek and Roth, Dan},
  title = {{Margin-based Decomposed Amortized Inference}},
  booktitle = {Annual meeting of the Association of Computational Linguistics (ACL)},
  year = {2013},
  tags = {Structured Learning and Prediction,Efficient machine learning,Integer linear programming,Inference},
  paper = {pdfs/kundu2013margin-based.pdf}
}

@inproceedings{huang2013multi-faceted,
  author = {Huang, Ruihong and Riloff, Ellen},
  title = {{Multi-faceted Event Recognition with Bootstrapped Dictionaries}},
  booktitle = { Proceedings of the 2013  Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2013)},
  year = {2013},
  tags = {Information Extraction,Events},
  paper = {pdfs/huang2013multi-faceted.pdf}
}

@inproceedings{huang2013classifying,
  author = {Huang, Ruihong and Riloff, Ellen},
  title = {{Classifying Message Board Posts with an Extracted Lexicon of Patient Attributes}},
  booktitle = { Proceedings of the 2013  Conference on Empirical Methods in Natural Language Processing (EMNLP 2013)},
  year = {2013},
  tags = {Information Extraction,Veternary},
  paper = {pdfs/huang2013classifying.pdf}
}

@article{goyal2013computational,
  author = {Goyal, Amit and Riloff, Ellen and Daume III, Hal},
  title = {{A Computational Model for Plot Units}},
  journal = {Computational Intelligence},
  year = {2013},
  volume = {29},
  tags = {Plot Units,Sentiment},
  paper = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-8640.2012.00455.x}
}

@inproceedings{gilbert2013domain-specific,
  author = {Gilbert, Nathan and Riloff, Ellen},
  title = {{Domain-Specific Coreference Resolution with Lexicalized Features}},
  booktitle = {Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013). },
  year = {2013},
  tags = {Coreference},
  paper = {pdfs/gilbert2013domain-specific.pdf}
}

@inproceedings{chang2013multi-core,
  author = {Chang, Kai-Wei and Srikumar, Vivek and Roth, Dan},
  title = {{Multi-core Structural SVM Training}},
  booktitle = {European Conference on Machine Learning (ECML)},
  year = {2013},
  tags = {Structured Learning and Prediction},
  paper = {pdfs/chang2013multi-core.pdf}
}

@inproceedings{srikumar2012on-amortizing,
  author = {Srikumar, Vivek and Kundu, Gourab and Roth, Dan},
  title = {{On Amortizing Inference Cost for Structured Prediction}},
  booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year = {2012},
  tags = {Structured Learning and Prediction,Inference,Integer linear programming,Efficient machine learning},
  paper = {pdfs/srikumar2012on-amortizing.pdf}
}

@unpublished{srikumar2012brief-introduction,
  author = {Srikumar, Vivek},
  title = {{A brief introduction to inference using Lagrangian Relaxation}},
  note = {Unpublished note},
  year = {2012},
  tags = {Expository notes,Tutorial,Inference},
  paper = {pdfs/srikumar2012brief-introduction.pdf}
}

@inproceedings{qadir2012ensemble-based,
  author = {Qadir, Ashequl and Riloff, Ellen},
  title = {{Ensemble-based Semantic Lexicon Induction for Semantic Tagging}},
  booktitle = {Proceedings of the First Joint Conference on Lexical and Computational Semantics (*SEM 2012)},
  year = {2012},
  tags = {Semantics,Coreference},
  paper = {pdfs/qadir2012ensemble-based.pdf},
  award = {Best Long Paper Award}
}

@inproceedings{huang2012modeling,
  author = {Huang, Ruihong and Riloff, Ellen},
  title = {{Modeling Textual Cohesion for Event Extraction}},
  booktitle = { Proceedings of the 26th Conference on Artificial Intelligence (AAAI 2012)},
  year = {2012},
  tags = {Information Extraction,Events},
  paper = {pdfs/huang2012modeling.pdf}
}

@inproceedings{huang2012bootstrapped,
  author = {Huang, Ruihong and Riloff, Ellen},
  title = {{Bootstrapped Training of Event Extraction Classifiers}},
  booktitle = { Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2012)},
  year = {2012},
  tags = {Information Extraction,Events},
  paper = {pdfs/huang2012bootstrapped.pdf}
}

@inproceedings{goldwasser2012predicting,
  author = {Goldwasser, Dan and Srikumar, Vivek and Roth, Dan},
  title = {{Predicting Structures in NLP: Constrained Conditional Models and Integer Linear Programming in NLP}},
  booktitle = {NAACL HLT Tutorial Abstracts},
  year = {2012},
  tags = {Tutorial,Structured Learning and Prediction,Integer linear programming},
  paper = {pdfs/goldwasser2012predicting.pdf}
}

@inproceedings{endres2012learning,
  author = {Endres, Ian and Srikumar, Vivek and Chang, Ming-Wei and Hoiem, Derek},
  title = {Learning Shared Body Plans},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2012},
  tags = {Structured Learning and Prediction},
  paper = {pdfs/endres2012learning.pdf}
}

@inproceedings{clarke2012nlp-curator,
  author = {Clarke, James and Srikumar, Vivek and Sammons, Mark and Roth, Dan},
  title = {{An NLP Curator (or: How I Learned to Stop Worrying and Love NLP Pipelines)}},
  booktitle = {Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  tags = {Software and Tools},
  paper = {pdfs/clarke2012nlp-curator.pdf}
}

@article{wiebe2011finding,
  author = {Wiebe, Janyce and Riloff, Ellen},
  title = {{Finding Mutual Benefit between Subjectivity Analysis and Information Extraction}},
  journal = {IEEE Transactions on Affective Computing},
  year = {2011},
  volume = {2},
  tags = {Information Extraction,Sentiment},
  paper = {http://www.computer.org/csdl/trans/ta/2011/04/tta2011040175-abs.html}
}

@inproceedings{srikumar2011joint-model,
  author = {Srikumar, Vivek and Roth, Dan},
  title = {{A Joint Model for Extended Semantic Role Labeling}},
  booktitle = {Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year = {2011},
  tags = {Semantic Role Labeling,Frame Semantics,Structured Learning and Prediction,Preposition Semantics,Integer linear programming,Inference},
  paper = {pdfs/srikumar2011joint-model.pdf}
}

@inproceedings{qadir2011classifying,
  author = {Qadir, Ashequl and Riloff, Ellen},
  title = {{Classifying Sentences as Speech Acts in Message Board Posts}},
  booktitle = {Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP 2011).},
  year = {2011},
  tags = {Speech Acts,Veternary},
  paper = {pdfs/qadir2011classifying.pdf}
}

@inproceedings{pokkunuri2011role-of,
  author = {Pokkunuri, Sandeep and Ramakrishnan, Cartic and Riloff, Ellen and Hovy, Eduard and Burns, Gully},
  title = {{The Role of Information Extraction in the Design of a Document Triage Application for Biocuration}},
  booktitle = {ACL 2011 Workshop on Biomedical Natural Language Processing (BioNLP 2011)},
  year = {2011},
  tags = {Information Extraction,Biocuration},
  paper = {pdfs/pokkunuri2011role-of.pdf}
}

@inproceedings{kim2011taming,
  author = {Kim, Youngjun and Riloff, Ellen and Gilbert, Nathan},
  title = {{The Taming of Reconcile as a Biomedical Coreference Resolver}},
  booktitle = {ACL 2011 Workshop on Biomedical Natural Language Processing (BioNLP 2011), Shared Task Paper},
  year = {2011},
  tags = {Coreference,Medicine},
  paper = {pdfs/kim2011taming.pdf}
}

@inproceedings{kim2011improving,
  author = {Kim, Youngjun and Riloff, Ellen and Meystre, Stéphane},
  title = {{Improving Classification of Medical Assertions in Clinical Notes}},
  booktitle = { Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL 2011).},
  year = {2011},
  tags = {Information Extraction,Medicine},
  paper = {pdfs/kim2011improving.pdf}
}

@inproceedings{huang2011peeling,
  author = {Huang, Ruihong and Riloff, Ellen},
  title = {{Peeling Back the Layers: Detecting Event Role Fillers in Secondary Contexts}},
  booktitle = { Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL 2011)},
  year = {2011},
  tags = {Information Extraction,Events},
  paper = {pdfs/huang2011peeling.pdf}
}

@techreport{stoyanov2010reconcile,
  author = {Stoyanov, Veselin and Cardie, Claire and Gilbert, Nathan and Riloff, Ellen and Buttler, David and Hysom, David},
  title = {{Reconcile: A Coreference Resolution Research Platform, Technical Report}},
  institution = {Lawrence Livermore National Lab. (LLNL)},
  number = {LLNL-TR-420722},
  year = {2010},
  tags = {Coreference},
  paper = {http://hdl.handle.net/1813/14919}
}

@inproceedings{stoyanov2010coreference,
  author = {Stoyanov, Veselin and Cardie, Claire and Gilbert, Nathan and Riloff, Ellen and Buttler, David and Hysom, David},
  title = {{Coreference Resolution with Reconcile}},
  booktitle = {Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010).},
  year = {2010},
  tags = {Coreference},
  paper = {pdfs/stoyanov2010coreference.pdf}
}

@inproceedings{ramakrishnan2010building,
  author = {Ramakrishnan, Cartic and Baumgartner Jr, William and Blake, Judith and Burns, Gully APC and Cohen, K. Bretonnel and Drabkin, Harold and Eppig, Janan and Hovy, Eduard and Hsu, Chun-Nan and Hunter, Lawrence and Ingulfsen, Tommy and Onda, Hiroaki and Pokkunuri, Sandeep and Riloff, Ellen and Roeder, Roeder and Verspoor, Karin},
  title = {{Building the Scientific Knowledge Mine (SciKnowMine): a community-driven framework for text mining tools in direct service to biocuration}},
  booktitle = { LREC-10 Workshop on New Challenges for NLP Frameworks},
  year = {2010},
  tags = {Information Extraction,Biocuration},
  paper = {pdfs/ramakrishnan2010building.pdf}
}

@inproceedings{huang2010inducing,
  author = {Huang, Ruihong and Riloff, Ellen},
  title = {{Inducing Domain-specific Semantic Class Taggers from (Almost) Nothing}},
  booktitle = {Proceedings of The 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010).},
  year = {2010},
  tags = {Semantics,Veternary},
  paper = {pdfs/huang2010inducing.pdf}
}

@inbook{hobbs2010handbook,
  author = {Hobbs, Jerry and Riloff, Ellen},
  editor = {Indurkhya, Nitin and Damerau, Fred J.},
  title = {Handbook of Natural Language Processing, 2nd Edition},
  chapter = {{Information Extraction}},
  publisher = {Chapman & Hall/CRC Press, Taylor & Francis Group},
  year = {2010},
  tags = {Information Extraction},
  paper = {pdfs/hobbs2010handbook.pdf}
}

@inproceedings{goyal2010toward,
  author = {Goyal, Amit and Riloff, Ellen and Daume III, Hal and Gilbert, Nathan},
  title = {{Toward Plot Units:  Automatic Affect State Analysis}},
  booktitle = {NAACL-HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text.},
  year = {2010},
  tags = {Plot Units,Sentiment},
  paper = {pdfs/goyal2010toward.pdf}
}

@inproceedings{goyal2010automatically,
  author = {Goyal, Amit and Riloff, Ellen and Daume III, Hal},
  title = {{Automatically Producing Plot Unit Representations for Narrative Text}},
  booktitle = {Proceedings of the 2010  Conference on Empirical Methods in Natural Language Processing (EMNLP 2010)},
  year = {2010},
  tags = {Plot Units,Sentiment},
  paper = {pdfs/goyal2010automatically.pdf}
}

@inproceedings{chang2010structured,
  author = {Chang, Ming-Wei and Srikumar, Vivek and Goldwasser, Dan and Roth, Dan},
  title = {{Structured Output Learning with Indirect Supervision}},
  booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
  year = {2010},
  tags = {Structured Learning and Prediction},
  paper = {pdfs/chang2010structured.pdf}
}

@inproceedings{chang2010discriminative,
  author = {Chang, Ming-Wei and Goldwasser, Dan and Roth, Dan and Srikumar, Vivek},
  title = {{Discriminative Learning over Constrained Latent Representations}},
  booktitle = {Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics},
  year = {2010},
  tags = {Structured Learning and Prediction,Textual entailment},
  paper = {pdfs/chang2010discriminative.pdf}
}

@inproceedings{stoyanov2009conundrums,
  author = {Stoyanov, Veselin and Gilbert, Nathan and Cardie, Claire and Riloff, Ellen},
  title = {{Conundrums in Noun Phrase Coreference Resolution: Making Sens-the-Art}},
  booktitle = { Proceedings of the Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL-IJCNLP 2009)},
  year = {2009},
  tags = {Coreference},
  paper = {pdfs/stoyanov2009conundrums.pdf}
}

@inproceedings{sammons2009relation,
  author = {Sammons, Mark and Vydiswaran, V.G. Vinod and Vieira, Tim and Johri, Nikhil and Chang, Ming-Wei and Goldwasser, Dan and Srikumar, Vivek and Kundu, Gourab and Tu, Yuancheng and Small, Kevin and Rule, Joshua and Do, Quang and Roth, Dan},
  title = {{Relation Alignment for Textual Entailment Recognition}},
  booktitle = {Text Analysis Conference (TAC)},
  year = {2009},
  tags = {Textual entailment},
  paper = {pdfs/sammons2009relation.pdf}
}

@inproceedings{patwardhan2009unified,
  author = {Patwardhan, Siddarth and Riloff, Ellen},
  title = {{A Unified Model of Phrasal and Sentential Evidence for Information Extraction}},
  booktitle = { Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (EMNLP-09)},
  year = {2009},
  tags = {Information Extraction,Events},
  paper = {pdfs/patwardhan2009unified.pdf}
}

@inproceedings{kozareva2009learning,
  author = {Kozareva, Zornitsa and Hovy, Eduard and Riloff, Ellen},
  title = {{Learning and Evaluating the Content and Structure of a Term Taxonomy}},
  booktitle = { AAAI-09 Spring Symposium on Learning by Reading ad Learning to Read. },
  year = {2009},
  tags = {Semantics},
  paper = {pdfs/kozareva2009learning.pdf}
}

@inproceedings{igo2009corpus-based,
  author = {Igo, Sean and Riloff, Ellen},
  title = {{Corpus-based Semantic Lexicon Induction with Web-based Corroboration}},
  booktitle = { NAACL-09 Workshop on Unsupervised and Minimally Supervised Learning of Lexical Semantics},
  year = {2009},
  tags = {Semantics},
  paper = {pdfs/igo2009corpus-based.pdf}
}

@inproceedings{hovy2009toward,
  author = {Hovy, Eduard and Kozareva, Zornitsa and Riloff, Ellen},
  title = {{Toward Completeness in Concept Extraction and Classification}},
  booktitle = {Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (EMNLP-09)},
  year = {2009},
  tags = {Semantics},
  paper = {pdfs/hovy2009toward.pdf}
}

@inproceedings{srikumar2008extraction,
  author = {Srikumar, Vivek and Reichart, Roi and Sammons, Mark and Rappoport, Ari and Roth, Dan},
  title = {{Extraction of Entailed Semantic Relations Through Syntax-based Comma Resolution}},
  booktitle = {Proceedings of ACL-08: HLT},
  year = {2008},
  tags = {Semantic Role Labeling,Frame Semantics,Datasets},
  paper = {pdfs/srikumar2008extraction.pdf}
}

@techreport{ratinov2008conceptual,
  author = {Ratinov, Lev and Roth, Dan and Srikumar, Vivek},
  title = {{Conceptual Search and Text Categorization}},
  institution = {University of Illinois},
  number = {UIUCDCS-R-2008-2932},
  year = {2008},
  tags = {Applied ML,Representations & Learning},
  paper = {pdfs/ratinov2008conceptual.pdf}
}

@inproceedings{liebald2008proactive,
  author = {Liebald, Benjamin and Roth, Dan and Shah, Neelay and Srikumar, Vivek},
  title = {{Proactive Intrusion Detection}},
  booktitle = {Proceedings of the National Conference on Artificial Intelligence (AAAI)},
  year = {2008},
  tags = {Applied ML},
  paper = {pdfs/liebald2008proactive.pdf}
}

@inproceedings{kozareva2008semantic,
  author = {Kozareva, Zornitsa and Riloff, Ellen and Hovy, Eduard},
  title = {{Semantic Class Learning from the Web with Hyponym Pattern Linkage Graphs}},
  booktitle = { Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-08).},
  year = {2008},
  tags = {Semantics},
  paper = {pdfs/kozareva2008semantic.pdf}
}

@inproceedings{igo2008learning,
  author = {Igo, Sean and Riloff, Ellen},
  title = {{Learning to Identify Reduced Passive Verb Phrases with a Shallow Parser}},
  booktitle = { Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI-08)},
  year = {2008},
  tags = {Shallow Parsing},
  paper = {pdfs/igo2008learning.pdf}
}

@inproceedings{chang2008importance,
  author = {Chang, Ming-Wei and Ratinov, Lev and Roth, Dan and Srikumar, Vivek},
  title = {{Importance of Semantic Represenation: Dataless Classification}},
  booktitle = {Proceedings of the National Conference on Artificial Intelligence (AAAI)},
  year = {2008},
  tags = {Applied ML,Representations & Learning},
  paper = {pdfs/chang2008importance.pdf}
}

@inproceedings{price2007study-to,
  author = {Price, David and Riloff, Ellen and Zachary, Joseph},
  title = {{A Study to Evaluate a Natural Language Interface for Computer Science Education}},
  booktitle = { AIED 2007 Workshop on Emerging Technologies for Inquiry-Based Learning in Science.  },
  year = {2007},
  tags = {Natural Language Interface,Java},
  paper = {pdfs/price2007study-to.pdf}
}

@inproceedings{phillips2007exploiting,
  author = {Phillips, William and Riloff, Ellen},
  title = {{Exploiting Role-Identifying Nouns and Expressions for Information Extraction}},
  booktitle = { Proceedings of the 2007 Conference on Recent Advances in Natural Language Processing (RANLP-07)},
  year = {2007},
  tags = {Information Extraction,Events},
  paper = {pdfs/phillips2007exploiting.pdf}
}

@inproceedings{patwardhan2007effective,
  author = {Patwardhan, Siddarth and Riloff, Ellen},
  title = {{Effective Information Extraction with Semantic Affinity Patterns and Relevant Regions}},
  booktitle = { Proceedings of the 2007 Conference on Empirical Methods in Natural Language Processing (EMNLP-07)},
  year = {2007},
  tags = {Information Extraction,Events},
  paper = {pdfs/patwardhan2007effective.pdf}
}

@techreport{liebald2007proactive,
  author = {Liebald, Benjamin and Roth, Dan and Shah, Neelay and Srikumar, Vivek},
  title = {{Proactive Detection of Insider Attacks}},
  institution = {University of Illinois},
  number = {UIUCDCS-R-2007-2879},
  year = {2007},
  tags = {Applied ML},
  paper = {pdfs/liebald2007proactive.pdf}
}

@inproceedings{riloff2006feature,
  author = {Riloff, Ellen and Patwardhan, Siddarth and Wiebe, Janyce},
  title = {{Feature Subsumption for Opinion Analysis}},
  booktitle = {Proceedings of the 2006 Conference  on Empirical Methods in Natural Language Processing (EMNLP-06)},
  year = {2006},
  tags = {Opinions},
  paper = {pdfs/riloff2006feature.pdf}
}

@inbook{riloff2006advances,
  author = {Riloff, Ellen and Mann, Gideon and Phillips, William},
  editor = {Strzalkowski, T. and Harabagiu, S.},
  title = {Advances in Open Domain Question Answering},
  chapter = {{Reverse-Engineering Question/Answer Collections from Ordinary Text}},
  publisher = {Springer Series: Text, Speech and Language Technology, Vol. 32.},
  year = {2006},
  tags = {Question Answering},
  paper = {pdfs/riloff2006advances.pdf}
}

@inproceedings{patwardhan2006learning,
  author = {Patwardhan, Siddarth and Riloff, Ellen},
  title = {{Learning Domain-Specific Information Extraction Patterns from the Web}},
  booktitle = { ACL 2006 Workshop on Information Extraction Beyond the Document},
  year = {2006},
  tags = {Information Extraction,Events},
  paper = {pdfs/patwardhan2006learning.pdf}
}

@inproceedings{wilson2005opinionfinder,
  author = {Wilson, Theresa and Hoffmann, Paul and Somasundaran, Swapna and Kessler, Jason and Wiebe, Janyce and Choi, Yejin and Cardie, Claire and Riloff, Ellen and Patwardhan, Siddarth},
  title = {{OpinionFinder: A System for Subjectivity Analysis}},
  booktitle = {Proceedings of EMNLP 2005 Interactive Demonstrations},
  year = {2005},
  tags = {Opinions},
  paper = {https://www.aclweb.org/anthology/H05-2018.pdf}
}

@inproceedings{wiebe2005creating,
  author = {Wiebe, Janyce and Riloff, Ellen},
  title = {{Creating Subjective and Objective Sentence Classifiers from Unannotated Texts}},
  booktitle = {Proceedings of the 6th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing-05), Invited Paper},
  year = {2005},
  tags = {Sentiment},
  paper = {pdfs/wiebe2005creating.pdf}
}

@inproceedings{riloff2005exploiting,
  author = {Riloff, Ellen and Wiebe, Janyce and Phillips, William},
  title = {{Exploiting Subjectivity Classification to Improve Information Extraction}},
  booktitle = { Proceedings of the 20th National Conference on Artificial Intelligence (AAAI 2005)},
  year = {2005},
  tags = {Information Extraction,Sentiment},
  paper = {pdfs/riloff2005exploiting.pdf}
}

@inproceedings{choi2005identifying,
  author = {Choi, Yejin and Cardie, Claire and Riloff, Ellen and Patwardhan, Siddarth},
  title = {{Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns}},
  booktitle = {Proceedings of the 2005 Human Language Technology Conference / Conference on Empirical Methods in Natural Language Processing (EMNLP 2005)},
  year = {2005},
  tags = {Opinions,Information Extraction},
  paper = {pdfs/choi2005identifying.pdf}
}

@inproceedings{riloff2004introduction,
  author = {Riloff, Ellen and Phillips, William},
  title = {{An Introduction to the Sundance and AutoSlog Systems}},
  booktitle = { University of Utah School of Computing Technical Report #UUCS-04-015},
  year = {2004},
  tags = {Shallow Parsing,Information Extraction},
  paper = {pdfs/riloff2004introduction.pdf}
}

@inproceedings{bean2004unsupervised,
  author = {Bean, David and Riloff, Ellen},
  title = {{Unsupervised Learning of Contextual Role Knowledge for Coreference Resolution}},
  booktitle = { Proceedings of the Human Language Technology Conference / North American Chapter of the Association for Computational Linguistics Annual Meeting (NAACL 2004)},
  year = {2004},
  tags = {Coreference,Information Extraction},
  paper = {pdfs/bean2004unsupervised.pdf}
}

@inproceedings{wiebe2003recognizing,
  author = {Wiebe, Janyce and Breck, Eric and Buckley, Chris and Cardie, Claire and Davis, Paul and Fraser, Bruce and Litman, Diane and Pierce, David and Riloff, Ellen and Wilson, Theresa and Day, David and Maybury, Mark},
  title = {{Recognizing and Organizing Opinions Expressed in the World Press}},
  booktitle = { AAAI Spring Symposium on New Directions in Question Answering },
  year = {2003},
  tags = {Opinions},
  paper = {pdfs/wiebe2003recognizing.pdf}
}

@inproceedings{riloff2003learninga,
  author = {Riloff, Ellen and Wiebe, Janyce and Wilson, Theresa},
  title = {{Learning Subjective Nouns Using Extraction Pattern Bootstrapping}},
  booktitle = {Proceedings of the Seventh Conference on Natural Language Learning (CoNLL-2003)},
  year = {2003},
  tags = {Sentiment,Information Extraction},
  paper = {pdfs/riloff2003learninga.pdf}
}

@inproceedings{riloff2003learning,
  author = {Riloff, Ellen and Wiebe, Janyce},
  title = {{Learning Extraction Patterns for Subjective Expressions}},
  booktitle = {Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing (EMNLP-03)},
  year = {2003},
  tags = {Sentiment,Information Extraction},
  paper = {pdfs/riloff2003learning.pdf}
}

@inproceedings{jones2003active,
  author = {Jones, Rosie and Ghani, Rayid and Mitchell, Tom and Riloff, Ellen},
  title = {{Active Learning for Information Extraction with Multiple View Feature Sets}},
  booktitle = { ECML-03 Workshop on Adaptive Text Extraction and Mining },
  year = {2003},
  tags = {Information Extraction,Active Learning},
  paper = {pdfs/jones2003active.pdf}
}

@inproceedings{wiebe2002nrrc-summer,
  author = {Wiebe, Janyce and Breck, Eric and Buckley, Chris and Cardie, Claire and Davis, Paul and Fraser, Bruce and Litman, Diane and Pierce, David and Riloff, Ellen and Wilson, Theresa},
  title = {{NRRC Summer Workshop on Multiple-Perspective Question Answering: Final Report }},
  year = {2002},
  tags = {Question Answering,Opinions},
  paper = {pdfs/wiebe2002nrrc-summer.pdf}
}

@inproceedings{thelen2002bootstrapping,
  author = {Thelen, Michael and Riloff, Ellen},
  title = {{A Bootstrapping Method for Learning Semantic Lexicons using Extraction Pattern Contexts}},
  booktitle = {Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP-02)},
  year = {2002},
  tags = {Semantics,Information Extraction},
  paper = {pdfs/thelen2002bootstrapping.pdf}
}

@inproceedings{riloff2002inducing,
  author = {Riloff, Ellen and Schafer, Charles and Yarowsky, David},
  title = {{Inducing Information Extraction Systems for New Languages via Cross-Language Projection}},
  booktitle = { Proceedings of the 19th International Conference on Computational Linguistics (COLING-02)},
  year = {2002},
  tags = {Information Extraction,Multilingual},
  paper = {pdfs/riloff2002inducing.pdf}
}

@inproceedings{phillips2002exploiting,
  author = {Phillips, William and Riloff, Ellen},
  title = {{Exploiting Strong Syntactic Heuristics and Co-Training to Learn Semantic Lexicons}},
  booktitle = {Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP-02)},
  year = {2002},
  tags = {Semantics,Co-Training},
  paper = {pdfs/phillips2002exploiting.pdf}
}

@article{light2001analyses,
  author = {Light, Marc and Mann, Gideon and Riloff, Ellen and Breck, Eric},
  title = {{Analyses for Elucidating Current Question Answering Technology}},
  journal = { Journal of Natural Language Engineering },
  year = {2001},
  volume = {7},
  tags = {Question Answering},
  paper = {pdfs/light2001analyses.pdf}
}

@inproceedings{breck2001looking,
  author = {Breck, Eric and Light, Marc and Mann, Gideon and Riloff, Ellen and Brown, Brianne and Anand, Pranav and Rooth, Mats and Thelen, Michael},
  title = {{Looking Under the Hood: Tools for Diagnosing Your Question Answering Engine}},
  booktitle = {  ACL-2001 Workshop on Open-Domain Question Answering},
  year = {2001},
  tags = {Question Answering},
  paper = {pdfs/breck2001looking.pdf}
}

@inproceedings{riloff2000rule-based,
  author = {Riloff, Ellen and Thelen, Michael},
  title = {{A Rule-based Question Answering System for Reading Comprehension Tests}},
  booktitle = { ANLP/NAACL-2000 Workshop on Reading Comprehension Tests as Evaluation for Computer-Based Language Understanding Systems},
  year = {2000},
  tags = {Question Answering},
  paper = {pdfs/riloff2000rule-based.pdf}
}

@inproceedings{price2000naturaljava,
  author = {Price, David and Riloff, Ellen and Zachary, Joseph and Harvey, Brandon},
  title = {{NaturalJava: A Natural Language Interface for Programming in Java}},
  booktitle = {Proceedings of the 2000 International Conference on  Intelligent User Interfaces},
  year = {2000},
  tags = {Natural Language Interface,Java},
  paper = {pdfs/price2000naturaljava.pdf}
}

@inbook{riloff1999natural,
  author = {Riloff, Ellen and Lorenzen, Jeffrey},
  editor = {Strzalkowski, Tomek},
  title = {Natural Language Information Retrieval},
  chapter = {{Extraction-based Text Categorization: Generating Domain-specific Role Relationships Automatically}},
  publisher = {Kluwer Academic Publishers},
  year = {1999},
  tags = {Text Categorization,Information Extraction},
  paper = {pdfs/riloff1999natural.pdf}
}

@inproceedings{riloff1999learning,
  author = {Riloff, Ellen and Jones, Rosie},
  title = {{Learning Dictionaries for Information Extraction by Multi-Level Bootstrapping}},
  booktitle = {Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99)},
  year = {1999},
  tags = {Information Extraction},
  paper = {pdfs/riloff1999learning.pdf},
  award = {AAAI Classic Paper Award, Honorable Mention, 2017}
}

@article{riloff1999corpus-based,
  author = {Riloff, Ellen and Shepherd, Jessica},
  title = {{A Corpus-Based Bootstrapping Algorithm for Semi-Automated Semantic Lexicon Construction}},
  journal = { Journal of Natural Language Engineering },
  year = {1999},
  volume = {5},
  tags = {Semantics},
  paper = {pdfs/riloff1999corpus-based.pdf}
}

@inbook{riloff1999computational,
  author = {Riloff, Ellen},
  editor = {Ram, Ashwin and Moorman, Kenneth},
  title = {Computational Models of Reading and Understanding},
  chapter = {{Information Extraction as a Stepping Stone toward Story Understanding}},
  publisher = {The MIT Press},
  year = {1999},
  tags = {Information Extraction},
  paper = {pdfs/riloff1999computational.pdf}
}

@inproceedings{jones1999bootstrapping,
  author = {Jones, Rosie and McCallum, Andrew and Nigam, Kamal and Riloff, Ellen},
  title = {{Bootstrapping for Text Learning Tasks}},
  booktitle = { IJCAI-99 Workshop on Text Mining: Foundations, Techniques, and Applications},
  year = {1999},
  tags = {Information Extraction},
  paper = {pdfs/jones1999bootstrapping.pdf}
}

@inproceedings{bean1999corpus-based,
  author = {Bean, David and Riloff, Ellen},
  title = {{Corpus-Based Identification of Non-Anaphoric Noun Phrases}},
  booktitle = { Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL 1999)},
  year = {1999},
  tags = {Coreference},
  paper = {pdfs/bean1999corpus-based.pdf}
}

@inproceedings{riloff1998empirical,
  author = {Riloff, Ellen and Schmelzenbach, Mark},
  title = {{An Empirical Approach to Conceptual Case Frame Acquisition}},
  booktitle = { Proceedings of the Sixth Workshop on Very Large Corpora (WVLC-98)},
  year = {1998},
  tags = {Information Extraction,Semantics},
  paper = {pdfs/riloff1998empirical.pdf}
}

@inproceedings{furnkranz1998case-study,
  author = {Furnkranz, Johannes and Mitchell, Tom and Riloff, Ellen},
  title = {{A Case Study in Using Linguistic Phrases for Text Categorization on the WWW}},
  booktitle = {AAAI/ICML Workshop on Learning for Text Categorization},
  year = {1998},
  tags = {Text Categorization,Information Extraction},
  paper = {pdfs/furnkranz1998case-study.pdf}
}

@inproceedings{riloff1997corpus-based,
  author = {Riloff, Ellen and Shepherd, Jessica},
  title = {{A Corpus-Based Approach for Building Semantic Lexicons}},
  booktitle = {Proceedings of the Second Conference on Empirical  Methods in Natural Language Processing (EMNLP-2)},
  year = {1997},
  tags = {Semantics},
  paper = {pdfs/riloff1997corpus-based.pdf}
}

@article{riloff1996empirical,
  author = {Riloff, Ellen},
  title = {{An Empirical Study of Automated Dictionary Construction for Information Extraction in Three Domains}},
  journal = {AI Journal},
  year = {1996},
  volume = {85},
  tags = {Information Extraction,Events},
  paper = {pdfs/riloff1996empirical.pdf}
}

@inbook{riloff1996connectionist,
  author = {Riloff, Ellen},
  editor = {Wermter, Stefan Riloff, Ellen and Scheler, Gabriele},
  title = {Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing},
  chapter = {{Using Learned Extraction Patterns for Text Classification}},
  publisher = {Springer-Verlag, Berlin},
  year = {1996},
  tags = {Text Categorization,Information Extraction},
  paper = {pdfs/riloff1996connectionist.pdf}
}

@inproceedings{riloff1996automatically,
  author = {Riloff, Ellen},
  title = {{Automatically Generating Extraction Patterns from Untagged Text}},
  booktitle = {Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96)},
  year = {1996},
  tags = {Information Extraction,Events},
  paper = {pdfs/riloff1996automatically.pdf}
}

@inproceedings{riloff1995little,
  author = {Riloff, Ellen},
  title = {{Little Words Can Make a Big Difference for Text Classification}},
  booktitle = { Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval  },
  year = {1995},
  tags = {Text Categorization,Information Extraction},
  paper = {pdfs/riloff1995little.pdf}
}

@phdthesis{riloff1994informationa,
  author = {Riloff, Ellen},
  title = {{Information Extraction as a Basis for Portable Text Classification Systems}},
  school = {Ph.D. Dissertation, Computer Science Department, University of Massachusetts Amherst},
  year = {1994},
  tags = {Information Extraction,Text Categorization},
  paper = {pdfs/riloff1994informationa.pdf}
}

@article{riloff1994information,
  author = {Riloff, Ellen and Lehnert, Wendy},
  title = {{Information Extraction as a Basis for High-Precision Text Classification}},
  journal = { ACM Transactions on Information Systems  },
  year = {1994},
  volume = {12},
  tags = {Text Categorization,Information Extraction},
  paper = {pdfs/riloff1994information.pdf}
}

@inproceedings{riloff1993automatically,
  author = {Riloff, Ellen},
  title = {{Automatically Constructing a Dictionary for Information Extraction Tasks}},
  booktitle = {Proceedings of the Eleventh National Conference on Artificial Intelligence (AAAI-93)},
  year = {1993},
  tags = {Information Extraction,Events},
  paper = {pdfs/riloff1993automatically.pdf},
  award = {AAAI Classic Paper Award, Honorable Mention, 2012}
}