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2024

  1. Jiefu Ou, Arda Uzunouglu, Benjamin Van Durme, and Daniel Khashabi. 2024. WorldAPIs: The World Is Worth How Many APIs? A Thought Experiment. In Preprint. [pdf] [bibtex]
  2. Zhengping Jiang, Jingyu Zhang, Nathaniel Weir, Seth Ebner, Miriam Wanner, Kate Sanders, Daniel Khashabi, Anqi Liu, and Benjamin Van Durme. 2024. Core: Robust Factual Precision Scoring with Informative Sub-Claim Identification. In Preprint. [pdf] [bibtex]
  3. Kate Sanders and Benjamin Van Durme. 2024. A Survey of Video Datasets for Grounded Event Understanding. In arXiv.org. [pdf] [bibtex]
  4. William Fleshman and Benjamin Van Durme. 2024. RE-AdaptIR: Improving Information Retrieval through Reverse Engineered Adaptation. In arXiv.org. [pdf] [bibtex]
  5. Abe Bohan Hou, Orion Weller, Guanghui Qin, Eugene Yang, Dawn Lawrie, Nils Holzenberger, Andrew Blair-Stanek, and Benjamin Van Durme. 2024. CLERC: A Dataset for Legal Case Retrieval and Retrieval-Augmented Analysis Generation. In Preprint. [pdf] [bibtex]
  6. Yunmo Chen, Tongfei Chen, Harsh Jhamtani, Patrick Xia, Richard Shin, Jason Eisner, and Benjamin Van Durme. 2024. Learning to Retrieve Iteratively for In-Context Learning. In arXiv.org. [pdf] [bibtex]
  7. William Fleshman and Benjamin Van Durme. 2024. RE-Adapt: Reverse Engineered Adaptation of Large Language Models. In arXiv.org. [pdf] [bibtex]
  8. Jingyu Zhang, Marc Marone, Tianjian Li, Benjamin Van Durme, and Daniel Khashabi. 2024. Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data. In arXiv.org. [pdf] [bibtex]
  9. Dongwei Jiang, Jingyu Zhang, Orion Weller, Nathaniel Weir, Benjamin Van Durme, and Daniel Khashabi. 2024. SELF-[IN]CORRECT: LLMs Struggle with Refining Self-Generated Responses. In arXiv.org. [pdf] [bibtex]
  10. William Fleshman, Aleem Khan, Marc Marone, and Benjamin Van Durme. 2024. AdapterSwap: Continuous Training of LLMs with Data Removal and Access-Control Guarantees. In arXiv.org. [pdf] [bibtex]
  11. Boshi Wang, Hao Fang, Jason Eisner, Benjamin Van Durme, and Yu Su. 2024. LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error. In arXiv.org. [pdf] [bibtex]
  12. Kevin Xu, Yeganeh Kordi, Kate Sanders, Yizhong Wang, Adam Byerly, Jingyu Zhang, Benjamin Van Durme, and Daniel Khashabi. 2024. Tur[k]ingBench: A Challenge Benchmark for Web Agents. In arXiv.org. [pdf] [bibtex]
  13. Jeffrey Cheng, Marc Marone, Orion Weller, Dawn Lawrie, Daniel Khashabi, and Benjamin Van Durme. 2024. Dated Data: Tracing Knowledge Cutoffs in Large Language Models. In arXiv.org. [pdf] [bibtex]
  14. Orion Weller, Benjamin Chang, Sean MacAvaney, Kyle Lo, Arman Cohan, Benjamin Van Durme, Dawn Lawrie, and Luca Soldaini. 2024. FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions. In arXiv.org. [pdf] [bibtex]
  15. Miriam Wanner, Seth Ebner, Zhengping Jiang, Mark Dredze, and Benjamin Van Durme. 2024. A Closer Look at Claim Decomposition. In STARSEM. [pdf] [bibtex]
  16. Kate Sanders, Nathaniel Weir, and Benjamin Van Durme. 2024. TV-TREES: Multimodal Entailment Trees for Neuro-Symbolic Video Reasoning. In arXiv.org. [pdf] [bibtex]
  17. Zhengping Jiang, Yining Lu, Hanjie Chen, Daniel Khashabi, Benjamin Van Durme, and Anqi Liu. 2024. RORA: Robust Free-Text Rationale Evaluation. In arXiv.org. [pdf] [bibtex]
  18. Nathaniel Weir, Kate Sanders, Orion Weller, Shreya Sharma, Dongwei Jiang, Zhengping Jiang, Bhavana Dalvi, Oyvind Tafjord, Peter Alexander Jansen, Peter Clark, and Benjamin Van Durme. 2024. Enhancing Systematic Decompositional Natural Language Inference Using Informal Logic. In arXiv.org. [pdf] [bibtex]
  19. Weiting Tan, Yunmo Chen, Tongfei Chen, Guanghui Qin, Haoran Xu, Heidi C. Zhang, Benjamin Van Durme, and Philipp Koehn. 2024. Streaming Sequence Transduction through Dynamic Compression. In arXiv.org. [pdf] [bibtex]
  20. William Gantt, Shabnam Behzad, Hannah YoungEun An, Yunmo Chen, Aaron Steven White, Benjamin Van Durme, and M. Yarmohammadi. 2024. MultiMUC: Multilingual Template Filling on MUC-4. In Conference of the European Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  21. Xinrui Zou, Ming Zhang, Nathaniel Weir, Benjamin Van Durme, and Nils Holzenberger. 2024. Reframing Tax Law Entailment as Analogical Reasoning. In arXiv.org. [pdf] [bibtex]
  22. Haoran Xu, Amr Sharaf, Yunmo Chen, Weiting Tan, Lingfeng Shen, Benjamin Van Durme, Kenton Murray, and Young Jin Kim. 2024. Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation. In arXiv.org. [pdf] [bibtex]

2023

  1. Sky CH-Wang, Benjamin Van Durme, Jason Eisner, and Chris Kedzie. 2023. Do Androids Know They’re Only Dreaming of Electric Sheep? In arXiv.org. [pdf] [bibtex]
  2. William Fleshman and Benjamin Van Durme. 2023. Toucan: Token-Aware Character Level Language Modeling. In arXiv.org. [pdf] [bibtex]
  3. Andrew Blair-Stanek, Nils Holzenberger, and Benjamin Van Durme. 2023. BLT: Can Large Language Models Handle Basic Legal Text? In arXiv.org. [pdf] [bibtex]
  4. Siddharth Vashishtha, Alexander Martin, William Gantt, Benjamin Van Durme, and Aaron Steven White. 2023. FAMuS: Frames Across Multiple Sources. In North American Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  5. Weiting Tan, Haoran Xu, Lingfeng Shen, Shuyue Stella Li, Kenton Murray, Philipp Koehn, Benjamin Van Durme, and Yunmo Chen. 2023. Narrowing the Gap between Zero- and Few-shot Machine Translation by Matching Styles. In arXiv.org. [pdf] [bibtex]
  6. Nikita Moghe, Patrick Xia, Jacob Andreas, J. Eisner, Benjamin Van Durme, and Harsh Jhamtani. 2023. Interpreting User Requests in the Context of Natural Language Standing Instructions. In arXiv.org. [pdf] [bibtex]
  7. Abe Bohan Hou, Jingyu Zhang, Tianxing He, Yichen Wang, Yung-Sung Chuang, Hongwei Wang, Lingfeng Shen, Benjamin Van Durme, Daniel Khashabi, and Yulia Tsvetkov. 2023. SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation. In North American Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  8. Guanghui Qin and Benjamin Van Durme. 2023. Nugget: Neural Agglomerative Embeddings of Text. In International Conference on Machine Learning. [pdf] [bibtex]
  9. Justin Payan, Swaroop Mishra, Mukul Singh, Carina Negreanu, Christian Poelitz, Chitta Baral, Subhro Roy, Rasika Chakravarthy, Benjamin Van Durme, and E. Nouri. 2023. InstructExcel: A Benchmark for Natural Language Instruction in Excel. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  10. Guanghui Qin, Corby Rosset, Ethan C. Chau, Nikhil Rao, and Benjamin Van Durme. 2023. Dodo: Dynamic Contextual Compression for Decoder-only LMs. In Preprint. [pdf] [bibtex]
  11. Yunmo Chen, William Gantt, Tongfei Chen, Aaron Steven White, and Benjamin Van Durme. 2023. A Unified View of Evaluation Metrics for Structured Prediction. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  12. K. Shridhar, Harsh Jhamtani, Hao Fang, Benjamin Van Durme, Jason Eisner, and Patrick Xia. 2023. SCREWS: A Modular Framework for Reasoning with Revisions. In arXiv.org. [pdf] [bibtex]
  13. Andrew Blair-Stanek, Nils Holzenberger, and Benjamin Van Durme. 2023. OpenAI Cribbed Our Tax Example, But Can GPT-4 Really Do Tax? In arXiv.org. [pdf] [bibtex]
  14. Orion Weller, Kyle Lo, David Wadden, Dawn J Lawrie, Benjamin Van Durme, Arman Cohan, and Luca Soldaini. 2023. When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasets. In Findings. [pdf] [bibtex]
  15. Samuel Barham, Orion Weller, Michelle Yuan, Kenton Murray, M. Yarmohammadi, Zhengping Jiang, Siddharth Vashishtha, Alexander Martin, Anqi Liu, Aaron Steven White, Jordan L. Boyd-Graber, and Benjamin Van Durme. 2023. MegaWika: Millions of reports and their sources across 50 diverse languages. In arXiv.org. [pdf] [bibtex]
  16. Kate Sanders, David Etter, Reno Kriz, and Benjamin Van Durme. 2023. MultiVENT: Multilingual Videos of Events with Aligned Natural Text. In arXiv.org. [pdf] [bibtex]
  17. Elias Stengel-Eskin, Kyle Rawlins, and Benjamin Van Durme. 2023. Zero and Few-shot Semantic Parsing with Ambiguous Inputs. In arXiv.org. [pdf] [bibtex]
  18. Dhruv Verma, Yash Kumar Lal, Shreyashee Sinha, Benjamin Van Durme, and Adam Poliak. 2023. Evaluating Paraphrastic Robustness in Textual Entailment Models. In Annual Meeting of the Association for Computational Linguistics. [pdf] [bibtex]
  19. Ishani Mondal, Michelle Yuan, N. Anandhavelu, Aparna Garimella, Francis Ferraro, Andrew Blair-Stanek, Benjamin Van Durme, and Jordan L. Boyd-Graber. 2023. InteractiveIE: Towards Assessing the Strength of Human-AI Collaboration in Improving the Performance of Information Extraction. In arXiv.org. [pdf] [bibtex]
  20. Orion Weller, Dawn J Lawrie, and Benjamin Van Durme. 2023. NevIR: Negation in Neural Information Retrieval. In Conference of the European Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  21. Orion Weller, Marc Marone, Nathaniel Weir, Dawn J Lawrie, Daniel Khashabi, and Benjamin Van Durme. 2023. “According to . . . ”: Prompting Language Models Improves Quoting from Pre-Training Data. In Conference of the European Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  22. Harsh Jhamtani, Hao Fang, Patrick Xia, Eran Levy, Jacob Andreas, and Benjamin Van Durme. 2023. Natural Language Decomposition and Interpretation of Complex Utterances. In arXiv.org. [pdf] [bibtex]
  23. Haoran Xu, Weiting Tan, Shuyue Stella Li, Yunmo Chen, Benjamin Van Durme, Philipp Koehn, and Kenton Murray. 2023. Condensing Multilingual Knowledge with Lightweight Language-Specific Modules. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  24. Marc Marone and Benjamin Van Durme. 2023. Data Portraits: Recording Foundation Model Training Data. In Neural Information Processing Systems. [pdf] [bibtex]
  25. Elias Stengel-Eskin and Benjamin Van Durme. 2023. Did You Mean...? Confidence-based Trade-offs in Semantic Parsing. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  26. Andrew Blair-Stanek, Nils Holzenberger, and Benjamin Van Durme. 2023. Can GPT-3 Perform Statutory Reasoning? In International Conference on Artificial Intelligence and Law. [pdf] [bibtex]
  27. Kate Sanders, David Etter, Reno Kriz, and Benjamin Van Durme. 2023. MultiVENT: Multilingual Videos of Events and Aligned Natural Text. In Neural Information Processing Systems. [pdf] [bibtex]
  28. Shabnam Behzad, Seth Ebner, Marc Marone, Benjamin Van Durme, and M. Yarmohammadi. 2023. The Effect of Alignment Correction on Cross-Lingual Annotation Projection. In Law. [pdf] [bibtex]

2022

  1. Zhuowan Li, Cihang Xie, Benjamin Van Durme, and Alan Yuille. 2022. Localization vs. Semantics: Visual Representations in Unimodal and Multimodal Models. In Conference of the European Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  2. Orion Weller, Aleem Khan, Nathaniel Weir, Dawn J Lawrie, and Benjamin Van Durme. 2022. Defending Against Disinformation Attacks in Open-Domain Question Answering. In Conference of the European Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  3. Kangda Wei, Dawn J Lawrie, Benjamin Van Durme, Yunmo Chen, and Orion Weller. 2022. When Do Decompositions Help for Machine Reading? In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  4. Nathaniel Weir, Ryan Thomas, Randolph D’Amore, Kellie Hill, Benjamin Van Durme, and Harsh Jhamtani. 2022. Ontologically Faithful Generation of Non-Player Character Dialogues. In arXiv.org. [pdf] [bibtex]
  5. Zhuowan Li, Xingrui Wang, Elias Stengel-Eskin, Adam Kortylewski, Wufei Ma, Benjamin Van Durme, Alan Yuille Johns Hopkins University, U. California, Max Planck Institute for Informatics, and U. Freiburg. 2022. Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning. In Computer Vision and Pattern Recognition. [pdf] [bibtex]
  6. Elias Stengel-Eskin, Jimena Guallar-Blasco, Yi Zhou, and Benjamin Van Durme. 2022. Why Did the Chicken Cross the Road? Rephrasing and Analyzing Ambiguous Questions in VQA. In Annual Meeting of the Association for Computational Linguistics. [pdf] [bibtex]
  7. Elias Stengel-Eskin and Benjamin Van Durme. 2022. Calibrated Interpretation: Confidence Estimation in Semantic Parsing. In Transactions of the Association for Computational Linguistics. [pdf] [bibtex]
  8. Kate Sanders, Reno Kriz, Anqi Liu, and Benjamin Van Durme. 2022. Ambiguous Images With Human Judgments for Robust Visual Event Classification. In Neural Information Processing Systems. [pdf] [bibtex]
  9. Yukun Feng, Patrick Xia, Benjamin Van Durme, and João Sedoc. 2022. Automatic Document Selection for Efficient Encoder Pretraining. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  10. Yunmo Chen, William Gantt, Weiwei Gu, Tongfei Chen, Aaron Steven White, and Benjamin Van Durme. 2022. Iterative Document-level Information Extraction via Imitation Learning. In Conference of the European Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  11. Weiwei Gu, Boyuan Zheng, Yunmo Chen, Tongfei Chen, and Benjamin Van Durme. 2022. An Empirical Study on Finding Spans. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  12. Patrick Xia and Benjamin Van Durme. 2022. Online Neural Coreference Resolution with Rollback. In Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference, pages 13–21, Gyeongju, Republic of Korea. Association for Computational Linguistics. [pdf] [bibtex]
  13. Nathaniel Weir and Benjamin Van Durme. 2022. NELLIE: A Neuro-Symbolic Inference Engine for Grounded, Compositional, and Explainable Reasoning. In Preprint. [pdf] [bibtex]
  14. Boyuan Zheng, Patrick Xia, M. Yarmohammadi, and Benjamin Van Durme. 2022. Multilingual Coreference Resolution in Multiparty Dialogue. In Transactions of the Association for Computational Linguistics. [pdf] [bibtex]
  15. Orion Weller, Marc Marone, Vladimir Braverman, Dawn Lawrie, and Benjamin Van Durme. 2022. Pretrained Models for Multilingual Federated Learning. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1413–1421, Seattle, United States. Association for Computational Linguistics. [pdf] [bibtex]
  16. Andrew Blair-stanek and Benjamin Van Durme. 2022. Improved Induction of Narrative Chains via Cross-Document Relations. In Proceedings of the 11th Joint Conference on Lexical and Computational Semantics, pages 208–212, Seattle, Washington. Association for Computational Linguistics. [pdf] [bibtex]
  17. Chenyu Zhang, Benjamin Van Durme, Zhuowan Li, and Elias Stengel-Eskin. 2022. Visual Commonsense in Pretrained Unimodal and Multimodal Models. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 5321–5335, Seattle, United States. Association for Computational Linguistics. [pdf] [bibtex]
  18. Ryan Volum, Sudha Rao, Michael Xu, Gabriel DesGarennes, Chris Brockett, Benjamin Van Durme, Olivia Deng, Akanksha Malhotra, and Bill Dolan. 2022. Craft an Iron Sword: Dynamically Generating Interactive Game Characters by Prompting Large Language Models Tuned on Code. In Proceedings of the 3rd Wordplay: When Language Meets Games Workshop (Wordplay 2022), pages 25–43, Seattle, United States. Association for Computational Linguistics. [pdf] [bibtex]
  19. Richard Shin and Benjamin Van Durme. 2022. Few-Shot Semantic Parsing with Language Models Trained on Code. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 5417–5425, Seattle, United States. Association for Computational Linguistics. [pdf] [bibtex]
  20. Subhro Roy, Sam Thomson, Tongfei Chen, Richard Shin, Adam Pauls, Jason Eisner, Benjamin Van Durme, Microsoft Semantic Machines, and Scaled Cognition. 2022. BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing. In Neural Information Processing Systems. [pdf] [bibtex]
  21. Noah Weber, Anton Belyy, Nils Holzenberger, Rachel Rudinger, and Benjamin Van Durme. 2022. Human Schema Curation via Causal Association Rule Mining. In Proceedings of the 16th Linguistic Annotation Workshop (LAW-XVI) within LREC2022, pages 139–150, Marseille, France. European Language Resources Association. [pdf] [bibtex]
  22. Nils Holzenberger, Yunmo Chen, and Benjamin Van Durme. 2022. Asking the Right Questions in Low Resource Template Extraction. In arXiv.org. [pdf] [bibtex]
  23. Elias Stengel-Eskin, Emmanouil Antonios Platanios, Adam Pauls, Sam Thomson, Hao Fang, Benjamin Van Durme, J. Eisner, and Yu Su. 2022. When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  24. Anton Belyy, Chieh-yang Huang, Jacob Andreas, Emmanouil Antonios Platanios, Sam Thomson, Richard Shin, Subhro Roy, Aleksandr Nisnevich, Charles Chen, and Benjamin Van Durme. 2022. Guided K-best Selection for Semantic Parsing Annotation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 114–126, Dublin, Ireland. Association for Computational Linguistics. [pdf] [bibtex]
  25. Kevin Yang, Olivia Deng, Charles Chen, Richard Shin, Subhro Roy, and Benjamin Van Durme. 2022. Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation. In Findings of the Association for Computational Linguistics: ACL 2022, pages 3685–3695, Dublin, Ireland. Association for Computational Linguistics. [pdf] [bibtex]
  26. Elias Stengel-Eskin and Benjamin Van Durme. 2022. The Curious Case of Control. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  27. Shijie Wu, Benjamin Van Durme, and Mark Dredze. 2022. Zero-shot Cross-lingual Transfer is Under-specified Optimization. In Proceedings of the 7th Workshop on Representation Learning for NLP, pages 236–248, Dublin, Ireland. Association for Computational Linguistics. [pdf] [bibtex]
  28. Michelle Yuan, Patrick Xia, Chandler May, Benjamin Van Durme, and Jordan Boyd-Graber. 2022. Adapting Coreference Resolution Models through Active Learning. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 7533–7549, Dublin, Ireland. Association for Computational Linguistics. [pdf] [bibtex]
  29. Nathaniel Weir, Xingdi Yuan, Marc-Alexandre Côté, Matthew J. Hausknecht, R. Laroche, I. Momennejad, H. V. Seijen, and Benjamin Van Durme. 2022. One-Shot Learning from a Demonstration with Hierarchical Latent Language. In Adaptive Agents and Multi-Agent Systems. [pdf] [bibtex]
  30. Guanghui Qin, Yukun Feng, and Benjamin Van Durme. 2022. The NLP Task Effectiveness of Long-Range Transformers. In Conference of the European Chapter of the Association for Computational Linguistics. [pdf] [bibtex]
  31. Subhro Roy, Sam Thomson, Tongfei Chen, Richard Shin, Adam Pauls, J. Eisner, and Benjamin Van Durme. 2022. BenchCLAMP: A Benchmark for Evaluating Language Models on Semantic Parsing. In arXiv.org. [pdf] [bibtex]
  32. Orion Weller, Aleem Khan, Nathaniel Weir, Dawn J Lawrie, and Benjamin Van Durme. 2022. Defending Against Poisoning Attacks in Open-Domain Question Answering. In arXiv.org. [pdf] [bibtex]
  33. Zhengping Jiang, Anqi Liu, and Benjamin Van Durme. 2022. Calibrating Zero-shot Cross-lingual (Un-)structured Predictions. In Conference on Empirical Methods in Natural Language Processing. [pdf] [bibtex]
  34. Zhuowan Li, Cihang Xie, Benjamin Van Durme, Alan Yuille Johns Hopkins University, U. California, and Santa Cruz. 2022. Localization vs. Semantics: How Can Language Benefit Visual Representation Learning? In arXiv.org. [pdf] [bibtex]
  35. Nathaniel Weir and Benjamin Van Durme. 2022. Dynamic Generation of Interpretable Inference Rules in a Neuro-Symbolic Expert System. In arXiv.org. [pdf] [bibtex]

2021

  1. Haoran Xu, Benjamin Van Durme, and Kenton Murray. 2021. BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 6663–6675, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics. [pdf] [bibtex]
  2. Richard Shin, Christopher Lin, Sam Thomson, Charles Chen, Subhro Roy, Emmanouil Antonios Platanios, Adam Pauls, Dan Klein, Jason Eisner, and Benjamin Van Durme. 2021. Constrained Language Models Yield Few-Shot Semantic Parsers. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 7699–7715, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics. [pdf] [bibtex]
  3. Patrick Xia and Benjamin Van Durme. 2021. Moving on from OntoNotes: Coreference Resolution Model Transfer. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 5241–5256, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics. [pdf] [bibtex]
  4. Mahsa Yarmohammadi, Shijie Wu, Marc Marone, Haoran Xu, Seth Ebner, Guanghui Qin, Yunmo Chen, Jialiang Guo, Craig Harman, Kenton Murray, Aaron Steven White, Mark Dredze, and Benjamin Van Durme. 2021. Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 1950–1967, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics. [pdf] [bibtex]
  5. Zhuowan Li, Elias Stengel-Eskin, Yixiao Zhang, Cihang Xie, Q. Tran, Benjamin Van Durme, and A. Yuille. 2021. Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images. In IEEE International Conference on Computer Vision. [pdf] [bibtex]
  6. Jiefu Ou, Nathaniel Weir, Anton Belyy, Felix Yu, and Benjamin Van Durme. 2021. InFillmore: Frame-Guided Language Generation with Bidirectional Context. In Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, pages 129–142, Online. Association for Computational Linguistics. [pdf] [bibtex]
  7. Nils Holzenberger and Benjamin Van Durme. 2021. Factoring Statutory Reasoning as Language Understanding Challenges. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 2742–2758, Online. Association for Computational Linguistics. [pdf] [bibtex]
  8. Thomas Lippincott and Ben Van Durme. 2021. Active learning and negative evidence for language identification. In Proceedings of the Second Workshop on Data Science with Human in the Loop: Language Advances, pages 47–51, Online. Association for Computational Linguistics. [pdf] [bibtex]
  9. Andrew Blair-Stanek and Benjamin Van Durme. 2021. AI for Tax Analogies and Code Renumbering. In Tax Law: Practitioner Series eJournal. [pdf] [bibtex]
  10. Patrick Xia, Guanghui Qin, Siddharth Vashishtha, Yunmo Chen, Tongfei Chen, Chandler May, Craig Harman, Kyle Rawlins, Aaron Steven White, and Benjamin Van Durme. 2021. LOME: Large Ontology Multilingual Extraction. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 149–159, Online. Association for Computational Linguistics. [pdf] [bibtex]
  11. Haoran Xu, Seth Ebner, Mahsa Yarmohammadi, Aaron Steven White, Benjamin Van Durme, and Kenton Murray. 2021. Gradual Fine-Tuning for Low-Resource Domain Adaptation. In Proceedings of the Second Workshop on Domain Adaptation for NLP, pages 214–221, Kyiv, Ukraine. Association for Computational Linguistics. [pdf] [bibtex]
  12. Elias Stengel-Eskin, Jimena Guallar-Blasco, and Benjamin Van Durme. 2021. Human-Model Divergence in the Handling of Vagueness. In Proceedings of the Society for Computation in Linguistics 2021, pages 390–393, Online. Association for Computational Linguistics. [pdf] [bibtex]
  13. Elias Stengel-Eskin, Jimena Guallar-Blasco, and Benjamin Van Durme. 2021. Human-Model Divergence in the Handling of Vagueness. In Proceedings of the Society for Computation in Linguistics 2021, pages 390–393, Online. Association for Computational Linguistics. [pdf] [bibtex]
  14. Luyu Gao, Zhuyun Dai, Tongfei Chen, Zhen Fan, Benjamin Van Durme, and Jamie Callan. 2021. Complement Lexical Retrieval Model with Semantic Residual Embeddings. In European Conference on Information Retrieval. [pdf] [bibtex]
  15. Elias Stengel-Eskin, Kenton Murray, Sheng Zhang, Aaron Steven White, and Benjamin Van Durme. 2021. Joint Universal Syntactic and Semantic Parsing. Transactions of the Association for Computational Linguistics, 9:756–773. [pdf] [bibtex]
  16. Ryan Culkin, J. Edward Hu, Elias Stengel-Eskin, Guanghui Qin, and Benjamin Van Durme. 2021. Iterative Paraphrastic Augmentation with Discriminative Span Alignment. Transactions of the Association for Computational Linguistics, 9:494–509. [pdf] [bibtex]

2020

  1. Michelle Yuan, Mozhi Zhang, Benjamin Van Durme, Leah Findlater, and Jordan Boyd-Graber. 2020. Interactive Refinement of Cross-Lingual Word Embeddings. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5984–5996, Online. Association for Computational Linguistics. [pdf] [bibtex]
  2. Yunmo Chen, Tongfei Chen, Seth Ebner, Aaron Steven White, and Benjamin Van Durme. 2020. Reading the Manual: Event Extraction as Definition Comprehension. In Proceedings of the Fourth Workshop on Structured Prediction for NLP, pages 74–83, Online. Association for Computational Linguistics. [pdf] [bibtex]
  3. Nathaniel Weir, João Sedoc, and Benjamin Van Durme. 2020. COD3S: Diverse Generation with Discrete Semantic Signatures. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5199–5211, Online. Association for Computational Linguistics. [pdf] [bibtex]
  4. Yunmo Chen, Tongfei Chen, and Benjamin Van Durme. 2020. Joint Modeling of Arguments for Event Understanding. In Proceedings of the First Workshop on Computational Approaches to Discourse, pages 96–101, Online. Association for Computational Linguistics. [pdf] [bibtex]
  5. Siddharth Vashishtha, Adam Poliak, Yash Kumar Lal, Benjamin Van Durme, and Aaron Steven White. 2020. Temporal Reasoning in Natural Language Inference. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4070–4078, Online. Association for Computational Linguistics. [pdf] [bibtex]
  6. Patrick Xia, João Sedoc, and Benjamin Van Durme. 2020. Incremental Neural Coreference Resolution in Constant Memory. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 8617–8624, Online. Association for Computational Linguistics. [pdf] [bibtex]
  7. Abhinav Singh, Patrick Xia, Guanghui Qin, Mahsa Yarmohammadi, and Benjamin Van Durme. 2020. CopyNext: Explicit Span Copying and Alignment in Sequence to Sequence Models. In Proceedings of the Fourth Workshop on Structured Prediction for NLP, pages 11–16, Online. Association for Computational Linguistics. [pdf] [bibtex]
  8. Patrick Xia, Shijie Wu, and Benjamin Van Durme. 2020. Which *BERT? A Survey Organizing Contextualized Encoders. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 7516–7533, Online. Association for Computational Linguistics. [pdf] [bibtex]
  9. Noah Weber, Rachel Rudinger, and Benjamin Van Durme. 2020. Causal Inference of Script Knowledge. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 7583–7596, Online. Association for Computational Linguistics. [pdf] [bibtex]
  10. Tongfei Chen, Zhengping Jiang, Adam Poliak, Keisuke Sakaguchi, and Benjamin Van Durme. 2020. Uncertain Natural Language Inference. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8772–8779, Online. Association for Computational Linguistics. [pdf] [bibtex]
  11. Elias Stengel-Eskin, Aaron Steven White, Sheng Zhang, and Benjamin Van Durme. 2020. Universal Decompositional Semantic Parsing. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8427–8439, Online. Association for Computational Linguistics. [pdf] [bibtex]
  12. Seth Ebner, Patrick Xia, Ryan Culkin, Kyle Rawlins, and Benjamin Van Durme. 2020. Multi-Sentence Argument Linking. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8057–8077, Online. Association for Computational Linguistics. [pdf] [bibtex]
  13. Anton Belyy and Benjamin Van Durme. 2020. Script Induction as Association Rule Mining. In Proceedings of the First Joint Workshop on Narrative Understanding, Storylines, and Events, pages 55–62, Online. Association for Computational Linguistics. [pdf] [bibtex]
  14. Tongfei Chen, Yunmo Chen, and Benjamin Van Durme. 2020. Hierarchical Entity Typing via Multi-level Learning to Rank. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8465–8475, Online. Association for Computational Linguistics. [pdf] [bibtex]
  15. Aaron Steven White, Elias Stengel-Eskin, Siddharth Vashishtha, Venkata Subrahmanyan Govindarajan, Dee Ann Reisinger, Tim Vieira, Keisuke Sakaguchi, Sheng Zhang, Francis Ferraro, Rachel Rudinger, Kyle Rawlins, and Benjamin Van Durme. 2020. The Universal Decompositional Semantics Dataset and Decomp Toolkit. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5698–5707, Marseille, France. European Language Resources Association. [pdf] [bibtex]
  16. Nils Holzenberger, Andrew Blair-Stanek, and Benjamin Van Durme. 2020. A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering. In NLLP@KDD. [pdf] [bibtex]
  17. Nathaniel Weir, Adam Poliak, and Benjamin Van Durme. 2020. Probing Neural Language Models for Human Tacit Assumptions. In Annual Meeting of the Cognitive Science Society. [pdf] [bibtex]
  18. Zhongyang Li, Xiao Ding, Ting Liu, J. Edward Hu, and Benjamin Van Durme. 2020. Guided Generation of Cause and Effect. In Christian Bessiere, editor, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020, pages 3629–3636. ijcai.org. [pdf] [bibtex]

2019

  1. Elias Stengel-Eskin, Tzu-ray Su, Matt Post, and Benjamin Van Durme. 2019. A Discriminative Neural Model for Cross-Lingual Word Alignment. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 910–920, Hong Kong, China. Association for Computational Linguistics. [pdf] [bibtex]
  2. J. Edward Hu, Abhinav Singh, Nils Holzenberger, Matt Post, and Benjamin Van Durme. 2019. Large-Scale, Diverse, Paraphrastic Bitexts via Sampling and Clustering. In Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), pages 44–54, Hong Kong, China. Association for Computational Linguistics. [pdf] [bibtex]
  3. Sheng Zhang, Xutai Ma, Kevin Duh, and Benjamin Van Durme. 2019. Broad-Coverage Semantic Parsing as Transduction. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 3786–3798, Hong Kong, China. Association for Computational Linguistics. [pdf] [bibtex]
  4. Seth Ebner, Felicity Wang, and Benjamin Van Durme. 2019. Bag-of-Words Transfer: Non-Contextual Techniques for Multi-Task Learning. In Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019), pages 40–46, Hong Kong, China. Association for Computational Linguistics. [pdf] [bibtex]
  5. Matthew Francis-Landau and Benjamin Van Durme. 2019. Exact and/or Fast Nearest Neighbors. In ArXiv. [pdf] [bibtex]
  6. Najoung Kim, Kyle Rawlins, Benjamin Van Durme, and Paul Smolensky. 2019. Predicting Argumenthood of English Preposition Phrases. In The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19). [pdf] [bibtex]
  7. Alex Wang, Jan Hula, Patrick Xia, Raghavendra Pappagari, R. Thomas McCoy, Roma Patel, Najoung Kim, Ian Tenney, Yinghui Huang, Katherin Yu, Shuning Jin, Berlin Chen, Benjamin Van Durme, Edouard Grave, Ellie Pavlick, and Samuel R. Bowman. 2019. Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4465–4476, Florence, Italy. Association for Computational Linguistics. [pdf] [bibtex]
  8. Zhongyang Li, Tongfei Chen, and Benjamin Van Durme. 2019. Learning to Rank for Plausible Plausibility. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4818–4823, Florence, Italy. Association for Computational Linguistics. [pdf] [bibtex]
  9. Siddharth Vashishtha, Benjamin Van Durme, and Aaron Steven White. 2019. Fine-Grained Temporal Relation Extraction. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2906–2919, Florence, Italy. Association for Computational Linguistics. [pdf] [bibtex]
  10. Yonatan Belinkov, Adam Poliak, Stuart Shieber, Benjamin Van Durme, and Alexander Rush. 2019. Don’t Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 877–891, Florence, Italy. Association for Computational Linguistics. [pdf] [bibtex]
  11. Sheng Zhang, Xutai Ma, Kevin Duh, and Benjamin Van Durme. 2019. AMR Parsing as Sequence-to-Graph Transduction. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 80–94, Florence, Italy. Association for Computational Linguistics. [pdf] [bibtex]
  12. Yonatan Belinkov, Adam Poliak, Stuart Shieber, Benjamin Van Durme, and Alexander Rush. 2019. On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 256–262, Minneapolis, Minnesota. Association for Computational Linguistics. [pdf] [bibtex]
  13. J. Edward Hu, Huda Khayrallah, Ryan Culkin, Patrick Xia, Tongfei Chen, Matt Post, and Benjamin Van Durme. 2019. Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 839–850, Minneapolis, Minnesota. Association for Computational Linguistics. [pdf] [bibtex]
  14. Najoung Kim, Roma Patel, Adam Poliak, Patrick Xia, Alex Wang, Tom McCoy, Ian Tenney, Alexis Ross, Tal Linzen, Benjamin Van Durme, Samuel R. Bowman, and Ellie Pavlick. 2019. Probing What Different NLP Tasks Teach Machines about Function Word Comprehension. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 235–249, Minneapolis, Minnesota. Association for Computational Linguistics. [pdf] [bibtex]
  15. Najoung Kim, Kyle Rawlins, Benjamin Van Durme, and Paul Smolensky. 2019. Predicting the Argumenthood of English Prepositional Phrases. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, pages 6578–6585. AAAI Press. [pdf] [bibtex]
  16. J. Edward Hu, Rachel Rudinger, Matt Post, and Benjamin Van Durme. 2019. PARABANK: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-Constrained Neural Machine Translation. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, pages 6521–6528. AAAI Press. [pdf] [bibtex]
  17. Yunmo Chen, Seth Ebner, Tongfei Chen, Patrick Xia, Elias Stengel-Eskin, Tzu-Ray Su, J. E. Hu, Nils Holzenberger, Ryan Culkin, Craig Harman, Max Thomas, Thomas Lippincott, A. White, Kyle Rawlins, and Benjamin Van Durme. 2019. NIST TAC SM-KBP 2019 System Description: JHU/UR Framework. In TAC. [pdf] [bibtex]
  18. Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R. Thomas McCoy, Najoung Kim, Benjamin Van Durme, Samuel R. Bowman, Dipanjan Das, and Ellie Pavlick. 2019. What do you learn from context? Probing for sentence structure in contextualized word representations. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019. OpenReview.net. [pdf] [bibtex]
  19. Venkata Govindarajan, Benjamin Van Durme, and Aaron Steven White. 2019. Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements. Transactions of the Association for Computational Linguistics, 7:501–517. [pdf] [bibtex]

2018

  1. Adam Poliak, Aparajita Haldar, Rachel Rudinger, J. Edward Hu, Ellie Pavlick, Aaron Steven White, and Benjamin Van Durme. 2018. Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 67–81, Brussels, Belgium. Association for Computational Linguistics. [pdf] [bibtex]
  2. Sheng Zhang, Xutai Ma, Rachel Rudinger, Kevin Duh, and Benjamin Van Durme. 2018. Cross-lingual Decompositional Semantic Parsing. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1664–1675, Brussels, Belgium. Association for Computational Linguistics. [pdf] [bibtex]
  3. Sheng Zhang, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Kevin Duh, and Benjamin Van Durme. 2018. ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension. In ArXiv. [pdf] [bibtex]
  4. Pushpendre Rastogi, Adam Poliak, V. Lyzinski, and Benjamin Van Durme. 2018. Neural variational entity set expansion for automatically populated knowledge graphs. In Information Retrieval Journal. [pdf] [bibtex]
  5. Rachel Rudinger, Adam Teichert, Ryan Culkin, Sheng Zhang, and Benjamin Van Durme. 2018. Neural-Davidsonian Semantic Proto-role Labeling. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 944–955, Brussels, Belgium. Association for Computational Linguistics. [pdf] [bibtex]
  6. Aaron Steven White, Rachel Rudinger, Kyle Rawlins, and Benjamin Van Durme. 2018. Lexicosyntactic Inference in Neural Models. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 4717–4724, Brussels, Belgium. Association for Computational Linguistics. [pdf] [bibtex]
  7. Pushpendre Rastogi, Adam Poliak, V. Lyzinski, and Benjamin Van Durme. 2018. Neural variational entity set expansion for automatically populated knowledge graphs. In Information Retrieval Journal. [pdf] [bibtex]
  8. Adam Poliak, Aparajita Haldar, Rachel Rudinger, J. Edward Hu, Ellie Pavlick, Aaron Steven White, and Benjamin Van Durme. 2018. Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 67–81, Brussels, Belgium. Association for Computational Linguistics. [pdf] [bibtex]
  9. Yonatan Belinkov, Adam Poliak, S. Shieber, and Benjamin Van Durme. 2018. Mitigating Bias in Natural Language Inference Using Adversarial Learning. In Preprint. [pdf] [bibtex]
  10. Keisuke Sakaguchi and Benjamin Van Durme. 2018. Efficient Online Scalar Annotation with Bounded Support. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 208–218, Melbourne, Australia. Association for Computational Linguistics. [pdf] [bibtex]
  11. Adam Poliak, Yonatan Belinkov, James Glass, and Benjamin Van Durme. 2018. On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 513–523, New Orleans, Louisiana. Association for Computational Linguistics. [pdf] [bibtex]
  12. Rachel Rudinger, Aaron Steven White, and Benjamin Van Durme. 2018. Neural Models of Factuality. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 731–744, New Orleans, Louisiana. Association for Computational Linguistics. [pdf] [bibtex]
  13. Sheng Zhang, Kevin Duh, and Benjamin Van Durme. 2018. Fine-grained Entity Typing through Increased Discourse Context and Adaptive Classification Thresholds. In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, pages 173–179, New Orleans, Louisiana. Association for Computational Linguistics. [pdf] [bibtex]
  14. Adam Poliak, Jason Naradowsky, Aparajita Haldar, Rachel Rudinger, and Benjamin Van Durme. 2018. Hypothesis Only Baselines in Natural Language Inference. In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, pages 180–191, New Orleans, Louisiana. Association for Computational Linguistics. [pdf] [bibtex]
  15. Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018. Gender Bias in Coreference Resolution. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 8–14, New Orleans, Louisiana. Association for Computational Linguistics. [pdf] [bibtex]
  16. Hongyuan Mei, Sheng Zhang, Kevin Duh, and Benjamin Van Durme. 2018. Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction. In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, pages 142–147, New Orleans, Louisiana. Association for Computational Linguistics. [pdf] [bibtex]
  17. Sheng Zhang, Kevin Duh, and Benjamin Van Durme. 2018. Cross-lingual Semantic Parsing. In Technical Report 937, Department of Computer Science, University of Rochester. [pdf] [bibtex]
  18. Adam Poliak, Aparajita Haldar, Rachel Rudinger, J. E. Hu, Ellie Pavlick, A. White, and Benjamin Van Durme. 2018. Towards a Unified Natural Language Inference Framework to Evaluate Sentence Representations. In ArXiv. [pdf] [bibtex]
  19. Patrick Xia, Elias Stengel-Eskin, Tongfei Chen, Seth Ebner, Nils Holzenberger, Ryan Culkin, Pushpendre Rastogi, Xutai Ma, and Benjamin Van Durme. 2018. NIST TAC SM-KBP 2018 System Description: JHU/UR Pipeline. In TAC. [pdf] [bibtex]
  20. T. Wolfe, Annabelle Carrell, Mark Dredze, and Benjamin Van Durme. 2018. Summarizing Entities using Distantly Supervised Information Extractors. In ProfS/KG4IR/Data:Search@SIGIR. [pdf] [bibtex]
  21. Rashmi Sankepally, Tongfei Chen, Benjamin Van Durme, and Douglas W. Oard. 2018. A Test Collection for Coreferent Mention Retrieval. In Kevyn Collins-Thompson, Qiaozhu Mei, Brian D. Davison, Yiqun Liu, and Emine Yilmaz, editors, The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR 2018, Ann Arbor, MI, USA, July 08-12, 2018, pages 1209–1212. ACM. [pdf] [bibtex]
  22. Michelle Yuan, Benjamin Van Durme, and Jordan L. Ying. 2018. Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages. In Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, and Roman Garnett, editors, Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, pages 8667–8677. [pdf] [bibtex]

2017

  1. Benjamin Van Durme, Tom Lippincott, Kevin Duh, Deana Burchfield, Adam Poliak, Cash Costello, Tim Finin, Scott Miller, James Mayfield, Philipp Koehn, Craig Harman, Dawn Lawrie, Chandler May, Max Thomas, Annabelle Carrell, Julianne Chaloux, Tongfei Chen, Alex Comerford, Mark Dredze, et al. 2017. CADET: Computer Assisted Discovery Extraction and Translation. In Proceedings of the IJCNLP 2017, System Demonstrations, pages 5–8, Tapei, Taiwan. Association for Computational Linguistics. [pdf] [bibtex]
  2. Aaron Steven White, Pushpendre Rastogi, Kevin Duh, and Benjamin Van Durme. 2017. Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 996–1005, Taipei, Taiwan. Asian Federation of Natural Language Processing. [pdf] [bibtex]
  3. Sheng Zhang, Kevin Duh, and Benjamin Van Durme. 2017. Selective Decoding for Cross-lingual Open Information Extraction. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 832–842, Taipei, Taiwan. Asian Federation of Natural Language Processing. [pdf] [bibtex]
  4. Keisuke Sakaguchi, Matt Post, and Benjamin Van Durme. 2017. Grammatical Error Correction with Neural Reinforcement Learning. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 366–372, Taipei, Taiwan. Asian Federation of Natural Language Processing. [pdf] [bibtex]
  5. Francis Ferraro, Adam Poliak, Ryan Cotterell, and Benjamin Van Durme. 2017. Frame-Based Continuous Lexical Semantics through Exponential Family Tensor Factorization and Semantic Proto-Roles. In Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017), pages 97–103, Vancouver, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  6. Nicholas Andrews, Mark Dredze, Benjamin Van Durme, and Jason Eisner. 2017. Bayesian Modeling of Lexical Resources for Low-Resource Settings. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1029–1039, Vancouver, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  7. Keisuke Sakaguchi, Matt Post, and Benjamin Van Durme. 2017. Error-repair Dependency Parsing for Ungrammatical Texts. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 189–195, Vancouver, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  8. Travis Wolfe, Mark Dredze, and Benjamin Van Durme. 2017. Pocket Knowledge Base Population. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 305–310, Vancouver, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  9. Sheng Zhang, Kevin Duh, and Benjamin Van Durme. 2017. MT/IE: Cross-lingual Open Information Extraction with Neural Sequence-to-Sequence Models. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 64–70, Valencia, Spain. Association for Computational Linguistics. [pdf] [bibtex]
  10. Tongfei Chen and Benjamin Van Durme. 2017. Discriminative Information Retrieval for Question Answering Sentence Selection. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 719–725, Valencia, Spain. Association for Computational Linguistics. [pdf] [bibtex]
  11. Adam Poliak, Pushpendre Rastogi, M. Patrick Martin, and Benjamin Van Durme. 2017. Efficient, Compositional, Order-sensitive n-gram Embeddings. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 503–508, Valencia, Spain. Association for Computational Linguistics. [pdf] [bibtex]
  12. Rachel Rudinger, Chandler May, and Benjamin Van Durme. 2017. Social Bias in Elicited Natural Language Inferences. In Proceedings of the First ACL Workshop on Ethics in Natural Language Processing, pages 74–79, Valencia, Spain. Association for Computational Linguistics. [pdf] [bibtex]
  13. Ryan Cotterell, Adam Poliak, Benjamin Van Durme, and Jason Eisner. 2017. Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 175–181, Valencia, Spain. Association for Computational Linguistics. [pdf] [bibtex]
  14. Aaron Steven White, Kyle Rawlins, and Benjamin Van Durme. 2017. The Semantic Proto-Role Linking Model. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 92–98, Valencia, Spain. Association for Computational Linguistics. [pdf] [bibtex]
  15. Chandler May, Kevin Duh, Benjamin Van Durme, and Ashwin Lall. 2017. Streaming Word Embeddings with the Space-Saving Algorithm. In ArXiv. [pdf] [bibtex]
  16. T. Wolfe, Mark Dredze, and Benjamin Van Durme. 2017. Feature Generation for Robust Semantic Role Labeling. In ArXiv. [pdf] [bibtex]
  17. Sheng Zhang, Rachel Rudinger, Kevin Duh, and Benjamin Van Durme. 2017. Ordinal Common-sense Inference. Transactions of the Association for Computational Linguistics, 5:379–395. [pdf] [bibtex]
  18. Adam R. Teichert, Adam Poliak, Benjamin Van Durme, and Matthew R. Gormley. 2017. Semantic Proto-Role Labeling. In Satinder P. Singh and Shaul Markovitch, editors, Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA, pages 4459–4466. AAAI Press. [pdf] [bibtex]
  19. Pushpendre Rastogi, Adam Poliak, and Benjamin Van Durme. 2017. Training Relation Embeddings under Logical Constraints. In KG4IR@SIGIR. [pdf] [bibtex]
  20. Pushpendre Rastogi and Benjamin Van Durme. 2017. Predicting Asymmetric Transitive Relations in Knowledge Bases. In KG4IR@SIGIR. [pdf] [bibtex]
  21. Keisuke Sakaguchi, Kevin Duh, Matt Post, and Benjamin Van Durme. 2017. Robsut Wrod Reocginiton via Semi-Character Recurrent Neural Network. In Satinder P. Singh and Shaul Markovitch, editors, Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA, pages 3281–3287. AAAI Press. [pdf] [bibtex]
  22. Mohamed Al-Badrashiny, Jason Bolton, Arun Tejasvi Chaganty, Kevin Clark, Craig Harman, Lifu Huang, Matthew Lamm, Jinhao Lei, Di Lu, Xiaoman Pan, Ashwin Paranjape, Ellie Pavlick, Haoruo Peng, Peng Qi, Pushpendre Rastogi, A. See, Kai Sun, Max Thomas, Chen-Tse Tsai, et al. 2017. TinkerBell: Cross-lingual Cold-Start Knowledge Base Construction. In TAC. [pdf] [bibtex]
  23. Sheng Zhang, Rachel Rudinger, and Benjamin Van Durme. 2017. An Evaluation of PredPatt and Open IE via Stage 1 Semantic Role Labeling. In IWCS 2017 — 12th International Conference on Computational Semantics — Short papers. [pdf] [bibtex]
  24. Rachel Rudinger, Kevin Duh, and Benjamin Van Durme. 2017. Skip-Prop: Representing Sentences with One Vector Per Proposition. In IWCS 2017 — 12th International Conference on Computational Semantics — Short papers. [pdf] [bibtex]

2016

  1. Aaron Steven White, Drew Reisinger, Keisuke Sakaguchi, Tim Vieira, Sheng Zhang, Rachel Rudinger, Kyle Rawlins, and Benjamin Van Durme. 2016. Universal Decompositional Semantics on Universal Dependencies. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 1713–1723, Austin, Texas. Association for Computational Linguistics. [pdf] [bibtex]
  2. Tom Lippincott and Benjamin Van Durme. 2016. Fluency detection on communication networks. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 1025–1029, Austin, Texas. Association for Computational Linguistics. [pdf] [bibtex]
  3. Travis Wolfe, Mark Dredze, and Benjamin Van Durme. 2016. A Study of Imitation Learning Methods for Semantic Role Labeling. In Proceedings of the Workshop on Structured Prediction for NLP, pages 44–53, Austin, TX. Association for Computational Linguistics. [pdf] [bibtex]
  4. Svitlana Volkova, I. Chetviorkin, Dustin L. Arendt, and Benjamin Van Durme. 2016. Contrasting Public Opinion Dynamics and Emotional Response During Crisis. In SocInfo. [pdf] [bibtex]
  5. Tongfei Chen and Benjamin Van Durme. 2016. Discriminative Information Retrieval for Knowledge Discovery. In ArXiv. [pdf] [bibtex]
  6. A. White, D. Reisinger, Rachel Rudinger, Kyle Rawlins, and Benjamin Van Durme. 2016. Computational linking theory. In ArXiv. [pdf] [bibtex]
  7. Chandler May, Ryan Cotterell, and Benjamin Van Durme. 2016. An Analysis of Lemmatization on Topic Models of Morphologically Rich Language. In arXiv: Computation and Language. [pdf] [bibtex]
  8. Pushpendre Rastogi and Benjamin Van Durme. 2016. A Critical Examination of RESCAL for Completion of Knowledge Bases with Transitive Relations. In ArXiv. [pdf] [bibtex]
  9. Svitlana Volkova, Yoram Bachrach, and Benjamin Van Durme. 2016. Mining User Interests to Predict Perceived Psycho-Demographic Traits on Twitter. In 2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService). [pdf] [bibtex]
  10. Francis Ferraro and Benjamin Van Durme. 2016. A Unified Bayesian Model of Scripts, Frames and Language. In Dale Schuurmans and Michael P. Wellman, editors, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA, pages 2601–2607. AAAI Press. [pdf] [bibtex]
  11. Rebecca Mason, Benjamin Gaska, Benjamin Van Durme, Pallavi Choudhury, Ted Hart, Bill Dolan, Kristina Toutanova, and Margaret Mitchell. 2016. Microsummarization of Online Reviews: An Experimental Study. In Dale Schuurmans and Michael P. Wellman, editors, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA, pages 3015–3021. AAAI Press. [pdf] [bibtex]
  12. Subbarao Kambhampati and Gerhard Brewka. 2016. Preface. In Subbarao Kambhampati, editor, Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9-15 July 2016, pages xxxiii–xxxiv. IJCAI/AAAI Press. [pdf] [bibtex]

2015

  1. Rachel Rudinger, Pushpendre Rastogi, Francis Ferraro, and Benjamin Van Durme. 2015. Script Induction as Language Modeling. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 1681–1686, Lisbon, Portugal. Association for Computational Linguistics. [pdf] [bibtex]
  2. Chandler May, Francis Ferraro, Alan McCree, Jonathan Wintrode, Daniel Garcia-Romero, and Benjamin Van Durme. 2015. Topic Identification and Discovery on Text and Speech. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 2377–2387, Lisbon, Portugal. Association for Computational Linguistics. [pdf] [bibtex]
  3. Pushpendre Rastogi and Benjamin Van Durme. 2015. Sublinear Partition Estimation. In ArXiv. [pdf] [bibtex]
  4. Ellie Pavlick, Johan Bos, Malvina Nissim, Charley Beller, Benjamin Van Durme, and Chris Callison-Burch. 2015. Adding Semantics to Data-Driven Paraphrasing. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1512–1522, Beijing, China. Association for Computational Linguistics. [pdf] [bibtex]
  5. Ellie Pavlick, Juri Ganitkevitch, Tsz Ping Chan, Xuchen Yao, Benjamin Van Durme, and Chris Callison-Burch. 2015. Domain-Specific Paraphrase Extraction. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 57–62, Beijing, China. Association for Computational Linguistics. [pdf] [bibtex]
  6. Ellie Pavlick, Pushpendre Rastogi, Juri Ganitkevitch, Benjamin Van Durme, and Chris Callison-Burch. 2015. PPDB 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 425–430, Beijing, China. Association for Computational Linguistics. [pdf] [bibtex]
  7. Ellie Pavlick, Travis Wolfe, Pushpendre Rastogi, Chris Callison-Burch, Mark Dredze, and Benjamin Van Durme. 2015. FrameNet+: Fast Paraphrastic Tripling of FrameNet. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 408–413, Beijing, China. Association for Computational Linguistics. [pdf] [bibtex]
  8. Nanyun Peng, Francis Ferraro, Mo Yu, Nicholas Andrews, Jay DeYoung, Max Thomas, Matthew R. Gormley, Travis Wolfe, Craig Harman, Benjamin Van Durme, and Mark Dredze. 2015. A Concrete Chinese NLP Pipeline. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pages 86–90, Denver, Colorado. Association for Computational Linguistics. [pdf] [bibtex]
  9. Rachel Rudinger, Vera Demberg, Ashutosh Modi, Benjamin Van Durme, and Manfred Pinkal. 2015. Learning to predict script events from domain-specific text. In Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics, pages 205–210, Denver, Colorado. Association for Computational Linguistics. [pdf] [bibtex]
  10. Svitlana Volkova, Benjamin Van Durme, David Yarowsky, and Yoram Bachrach. 2015. Social Media Predictive Analytics. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts, page 9, Denver, Colorado. Association for Computational Linguistics. [pdf] [bibtex]
  11. T. Wolfe, Mark Dredze, J. Mayfield, P. McNamee, Craig Harman, Timothy W. Finin, and Benjamin Van Durme. 2015. Interactive Knowledge Base Population. In ArXiv. [pdf] [bibtex]
  12. Travis Wolfe, Mark Dredze, and Benjamin Van Durme. 2015. Predicate Argument Alignment using a Global Coherence Model. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 11–20, Denver, Colorado. Association for Computational Linguistics. [pdf] [bibtex]
  13. Pushpendre Rastogi, Benjamin Van Durme, and Raman Arora. 2015. Multiview LSA: Representation Learning via Generalized CCA. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 556–566, Denver, Colorado. Association for Computational Linguistics. [pdf] [bibtex]
  14. Svitlana Volkova and Benjamin Van Durme. 2015. Online Bayesian Models for Personal Analytics in Social Media. In Blai Bonet and Sven Koenig, editors, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, 2015, Austin, Texas, USA, pages 2325–2331. AAAI Press. [pdf] [bibtex]
  15. Keith Levin, Aren Jansen, and Benjamin Van Durme. 2015. Segmental acoustic indexing for zero resource keyword search. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19-24, 2015, pages 5828–5832. IEEE. [pdf] [bibtex]
  16. Drew Reisinger, Rachel Rudinger, Francis Ferraro, Craig Harman, Kyle Rawlins, and Benjamin Van Durme. 2015. Semantic Proto-Roles. Transactions of the Association for Computational Linguistics, 3:475–488. [pdf] [bibtex]

2014

  1. Charley Beller, Craig Harman, and Benjamin Van Durme. 2014. Predicting Fine-grained Social Roles with Selectional Preferences. In Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science, pages 50–55, Baltimore, MD, USA. Association for Computational Linguistics. [pdf] [bibtex]
  2. Charley Beller, Rebecca Knowles, Craig Harman, Shane Bergsma, Margaret Mitchell, and Benjamin Van Durme. 2014. I’m a Belieber: Social Roles via Self-identification and Conceptual Attributes. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 181–186, Baltimore, Maryland. Association for Computational Linguistics. [pdf] [bibtex]
  3. Xuchen Yao and Benjamin Van Durme. 2014. Information Extraction over Structured Data: Question Answering with Freebase. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 956–966, Baltimore, Maryland. Association for Computational Linguistics. [pdf] [bibtex]
  4. Keisuke Sakaguchi, Matt Post, and Benjamin Van Durme. 2014. Efficient Elicitation of Annotations for Human Evaluation of Machine Translation. In Proceedings of the Ninth Workshop on Statistical Machine Translation, pages 1–11, Baltimore, Maryland, USA. Association for Computational Linguistics. [pdf] [bibtex]
  5. Svitlana Volkova, Glen Coppersmith, and Benjamin Van Durme. 2014. Inferring User Political Preferences from Streaming Communications. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 186–196, Baltimore, Maryland. Association for Computational Linguistics. [pdf] [bibtex]
  6. Jacqueline Aguilar, Charley Beller, Paul McNamee, Benjamin Van Durme, Stephanie Strassel, Zhiyi Song, and Joe Ellis. 2014. A Comparison of the Events and Relations Across ACE, ERE, TAC-KBP, and FrameNet Annotation Standards. In Proceedings of the Second Workshop on EVENTS: Definition, Detection, Coreference, and Representation, pages 45–53, Baltimore, Maryland, USA. Association for Computational Linguistics. [pdf] [bibtex]
  7. Matthew R. Gormley, Margaret Mitchell, Benjamin Van Durme, and Mark Dredze. 2014. Low-Resource Semantic Role Labeling. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1177–1187, Baltimore, Maryland. Association for Computational Linguistics. [pdf] [bibtex]
  8. Chandler May, Alex Clemmer, and Benjamin Van Durme. 2014. Particle Filter Rejuvenation and Latent Dirichlet Allocation. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 446–451, Baltimore, Maryland. Association for Computational Linguistics. [pdf] [bibtex]
  9. Xuchen Yao, Jonathan Berant, and Benjamin Van Durme. 2014. Freebase QA: Information Extraction or Semantic Parsing? In Proceedings of the ACL 2014 Workshop on Semantic Parsing, pages 82–86, Baltimore, MD. Association for Computational Linguistics. [pdf] [bibtex]
  10. Miles Osborne, Ashwin Lall, and Benjamin Van Durme. 2014. Exponential Reservoir Sampling for Streaming Language Models. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 687–692, Baltimore, Maryland. Association for Computational Linguistics. [pdf] [bibtex]
  11. Rachel Rudinger and Benjamin Van Durme. 2014. Is the Stanford Dependency Representation Semantic? In Proceedings of the Second Workshop on EVENTS: Definition, Detection, Coreference, and Representation, pages 54–58, Baltimore, Maryland, USA. Association for Computational Linguistics. [pdf] [bibtex]
  12. Pushpendre Rastogi and Benjamin Van Durme. 2014. Augmenting FrameNet Via PPDB. In Proceedings of the Second Workshop on EVENTS: Definition, Detection, Coreference, and Representation, pages 1–5, Baltimore, Maryland, USA. Association for Computational Linguistics. [pdf] [bibtex]
  13. Alex B. Fine, Austin F. Frank, T. Florian Jaeger, and Benjamin Van Durme. 2014. Biases in Predicting the Human Language Model. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 7–12, Baltimore, Maryland. Association for Computational Linguistics. [pdf] [bibtex]
  14. Jennifer Drexler, Pushpendre Rastogi, Jacqueline Aguilar, Benjamin Van Durme, and Matt Post. 2014. A Wikipedia-based Corpus for Contextualized Machine Translation. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14), pages 3593–3596, Reykjavik, Iceland. European Language Resources Association (ELRA). [pdf] [bibtex]
  15. Adrian Benton, Jay DeYoung, Adam R. Teichert, Stephen Mayhew, Mark Dredze, Benjamin Van Durme, and Max Thomas. 2014. Faster (and Better) Entity Linking with Cascades. In NIPS Workshop on Automated Knowledge Base Construction (ABKC). [pdf] [bibtex]
  16. Francis Ferraro, Max Thomas, Matthew R. Gormley, T. Wolfe, Craig Harman, and Benjamin Van Durme. 2014. Concretely Annotated Corpora. In Preprint. [pdf] [bibtex]

2013

  1. Xuchen Yao, Benjamin Van Durme, Chris Callison-Burch, and Peter Clark. 2013. Semi-Markov Phrase-Based Monolingual Alignment. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pages 590–600, Seattle, Washington, USA. Association for Computational Linguistics. [pdf] [bibtex]
  2. Margaret Mitchell, Jacqui Aguilar, Theresa Wilson, and Benjamin Van Durme. 2013. Open Domain Targeted Sentiment. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pages 1643–1654, Seattle, Washington, USA. Association for Computational Linguistics. [pdf] [bibtex]
  3. Jonathan Gordon and Benjamin Van Durme. 2013. Reporting bias and knowledge acquisition. In AKBC ’13. [pdf] [bibtex]
  4. Travis Wolfe, Benjamin Van Durme, Mark Dredze, Nicholas Andrews, Charley Beller, Chris Callison-Burch, Jay DeYoung, Justin Snyder, Jonathan Weese, Tan Xu, and Xuchen Yao. 2013. PARMA: A Predicate Argument Aligner. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 63–68, Sofia, Bulgaria. Association for Computational Linguistics. [pdf] [bibtex]
  5. Xuchen Yao, Benjamin Van Durme, Chris Callison-Burch, and Peter Clark. 2013. A Lightweight and High Performance Monolingual Word Aligner. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 702–707, Sofia, Bulgaria. Association for Computational Linguistics. [pdf] [bibtex]
  6. Shane Bergsma and Benjamin Van Durme. 2013. Using Conceptual Class Attributes to Characterize Social Media Users. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 710–720, Sofia, Bulgaria. Association for Computational Linguistics. [pdf] [bibtex]
  7. Xuchen Yao, Benjamin Van Durme, and Peter Clark. 2013. Automatic Coupling of Answer Extraction and Information Retrieval. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 159–165, Sofia, Bulgaria. Association for Computational Linguistics. [pdf] [bibtex]
  8. Xuchen Yao, Benjamin Van Durme, Chris Callison-Burch, and Peter Clark. 2013. Answer Extraction as Sequence Tagging with Tree Edit Distance. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 858–867, Atlanta, Georgia. Association for Computational Linguistics. [pdf] [bibtex]
  9. Jonathan Gordon and Benjamin Van Durme. 2013. Reporting Bias and Knowledge Extraction. In Preprint. [pdf] [bibtex]
  10. Shane Bergsma, Mark Dredze, Benjamin Van Durme, Theresa Wilson, and David Yarowsky. 2013. Broadly Improving User Classification via Communication-Based Name and Location Clustering on Twitter. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1010–1019, Atlanta, Georgia. Association for Computational Linguistics. [pdf] [bibtex]
  11. Juri Ganitkevitch, Benjamin Van Durme, and Chris Callison-Burch. 2013. PPDB: The Paraphrase Database. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 758–764, Atlanta, Georgia. Association for Computational Linguistics. [pdf] [bibtex]
  12. Martha Palmer, Ivan Titov, and Shumin Wu. 2013. Semantic Role Labeling. In NAACL HLT 2013 Tutorial Abstracts, pages 10–12, Atlanta, Georgia. Association for Computational Linguistics. [pdf] [bibtex]
  13. Martha Palmer, Ivan Titov, and Shumin Wu. 2013. Semantic Role Labeling. In NAACL HLT 2013 Tutorial Abstracts, pages 10–12, Atlanta, Georgia. Association for Computational Linguistics. [pdf] [bibtex]
  14. Francis Ferraro, Benjamin Van Durme, and Yanif Ahmad. 2013. Evaluating Progress in Probabilistic Programming through Topic Models. In Preprint. [pdf] [bibtex]
  15. David Etter, Francis Ferraro, Ryan Cotterell, Olivia Buzek, and Benjamin Van Durme. 2013. Nerit: Named Entity Recognition for Informal Text. In Human Language Technology Center of Excellence, Johns Hopkins, vol. Technical Report 11 (2013). [pdf] [bibtex]

2012

  1. Vinodkumar Prabhakaran, Michael Bloodgood, Mona Diab, Bonnie Dorr, Lori Levin, Christine D. Piatko, Owen Rambow, and Benjamin Van Durme. 2012. Statistical Modality Tagging from Rule-based Annotations and Crowdsourcing. In Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics, pages 57–64, Jeju, Republic of Korea. Association for Computational Linguistics. [pdf] [bibtex]
  2. Benjamin Van Durme. 2012. Streaming Analysis of Discourse Participants. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 48–58, Jeju Island, Korea. Association for Computational Linguistics. [pdf] [bibtex]
  3. Francis Ferraro, Benjamin Van Durme, and Matt Post. 2012. Toward Tree Substitution Grammars with Latent Annotations. In Proceedings of the NAACL-HLT Workshop on the Induction of Linguistic Structure, pages 23–30, Montréal, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  4. Francis Ferraro, Matt Post, and Benjamin Van Durme. 2012. Judging Grammaticality with Count-Induced Tree Substitution Grammars. In Proceedings of the Seventh Workshop on Building Educational Applications Using NLP, pages 116–121, Montréal, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  5. Courtney Napoles, Matthew Gormley, and Benjamin Van Durme. 2012. Annotated Gigaword. In Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction (AKBC-WEKEX), pages 95–100, Montréal, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  6. Brian Kjersten and Benjamin Van Durme. 2012. Space Efficiencies in Discourse Modeling via Conditional Random Sampling. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 513–517, Montréal, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  7. Xuchen Yao, Benjamin Van Durme, and Chris Callison-Burch. 2012. Expectations of Word Sense in Parallel Corpora. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 621–625, Montréal, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  8. Matthew R. Gormley, Mark Dredze, Benjamin Van Durme, and Jason Eisner. 2012. Shared Components Topic Models. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 783–792, Montréal, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  9. Benjamin Van Durme. 2012. Jerboa: A Toolkit for Randomized and Streaming Algorithms. In Technical Report 7, Human Language Technology Center of Excellence. [pdf] [bibtex]
  10. Juri Ganitkevitch, Benjamin Van Durme, and Chris Callison-Burch. 2012. Monolingual Distributional Similarity for Text-to-Text Generation. In *SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012), pages 256–264, Montréal, Canada. Association for Computational Linguistics. [pdf] [bibtex]
  11. A. Jansen, Benjamin Van Durme, and P. Clark. 2012. The JHU-HLTCOE Spoken Web Search System for MediaEval 2012. In MediaEval. [pdf] [bibtex]
  12. A. Jansen and Benjamin Van Durme. 2012. Indexing Raw Acoustic Features for Scalable Zero Resource Search. In INTERSPEECH. [pdf] [bibtex]

2011

  1. A. Jansen and Benjamin Van Durme. 2011. Efficient spoken term discovery using randomized algorithms. In 2011 IEEE Workshop on Automatic Speech Recognition & Understanding. [pdf] [bibtex]
  2. Tsz Ping Chan, Chris Callison-Burch, and Benjamin Van Durme. 2011. Reranking Bilingually Extracted Paraphrases Using Monolingual Distributional Similarity. In Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics, pages 33–42, Edinburgh, UK. Association for Computational Linguistics. [pdf] [bibtex]
  3. Juri Ganitkevitch, Chris Callison-Burch, Courtney Napoles, and Benjamin Van Durme. 2011. Learning Sentential Paraphrases from Bilingual Parallel Corpora for Text-to-Text Generation. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 1168–1179, Edinburgh, Scotland, UK. Association for Computational Linguistics. [pdf] [bibtex]
  4. Courtney Napoles, Chris Callison-Burch, Juri Ganitkevitch, and Benjamin Van Durme. 2011. Paraphrastic Sentence Compression with a Character-based Metric: Tightening without Deletion. In Proceedings of the Workshop on Monolingual Text-To-Text Generation, pages 84–90, Portland, Oregon. Association for Computational Linguistics. [pdf] [bibtex]
  5. Houda Bouamor, Aurélien Max, Gabriel Illouz, and Anne Vilnat. 2011. Web-based Validation for Contextual Targeted Paraphrasing. In Proceedings of the Workshop on Monolingual Text-To-Text Generation, pages 10–19, Portland, Oregon. Association for Computational Linguistics. [pdf] [bibtex]
  6. Courtney Napoles, Benjamin Van Durme, and Chris Callison-Burch. 2011. Evaluating Sentence Compression: Pitfalls and Suggested Remedies. In Proceedings of the Workshop on Monolingual Text-To-Text Generation, pages 91–97, Portland, Oregon. Association for Computational Linguistics. [pdf] [bibtex]
  7. Benjamin Van Durme and Ashwin Lall. 2011. Efficient Online Locality Sensitive Hashing via Reservoir Counting. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 18–23, Portland, Oregon, USA. Association for Computational Linguistics. [pdf] [bibtex]
  8. Byung Gyu Ahn, Benjamin Van Durme, and Chris Callison-Burch. 2011. WikiTopics: What is Popular on Wikipedia and Why. In Proceedings of the Workshop on Automatic Summarization for Different Genres, Media, and Languages, pages 33–40, Portland, Oregon. Association for Computational Linguistics. [pdf] [bibtex]
  9. Xuchen Yao and Benjamin Van Durme. 2011. Nonparametric Bayesian Word Sense Induction. In Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing, pages 10–14, Portland, Oregon. Association for Computational Linguistics. [pdf] [bibtex]
  10. R. Azevedo, Gautam Biswas, D. Bohus, Ted Carmichael, Mark A. Finlayson, M. Hadzikadic, Catherine Havasi, E. Horvitz, T. Kanda, O. Koyejo, W. Lawless, D. Lenat, Felipe Meneguzzi, Bilge Mutlu, Jean Oh, R. Pirrone, Antoine Raux, D. Sofge, G. Sukthankar, et al. 2011. Reports of the AAAI 2010 Fall Symposia. In AI Mag. [pdf] [bibtex]
  11. Shane Bergsma and Benjamin Van Durme. 2011. Learning Bilingual Lexicons Using the Visual Similarity of Labeled Web Images. In Toby Walsh, editor, IJCAI 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Barcelona, Catalonia, Spain, July 16-22, 2011, pages 1764–1769. IJCAI/AAAI. [pdf] [bibtex]
  12. Matthew R. Gormley, Mark Dredze, Benjamin Van Durme, and Jason Eisner. 2011. Shared Components Topic Models with Application to Selectional Preference. In NIPS Workshop on Learning Semantics. [pdf] [bibtex]

2010

  1. Lenhart K. Schubert, Benjamin Van Durme, and Marzieh Bazrafshan. 2010. Entailment Inference in a Natural Logic-like General Reasoner. In AAAI Fall Symposium: Commonsense Knowledge. [pdf] [bibtex]
  2. Benjamin Van Durme and Ashwin Lall. 2010. Online Generation of Locality Sensitive Hash Signatures. In Proceedings of the ACL 2010 Conference Short Papers, pages 231–235, Uppsala, Sweden. Association for Computational Linguistics. [pdf] [bibtex]
  3. Jonathan Gordon, Benjamin Van Durme, and Lenhart Schubert. 2010. Evaluation of Commonsense Knowledge with Mechanical Turk. In Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk, pages 159–162, Los Angeles. Association for Computational Linguistics. [pdf] [bibtex]
  4. Jonathan Gordon, Benjamin Van Durme, and Lenhart K. Schubert. 2010. Learning from the Web: Extracting General World Knowledge from Noisy Text. In Collaboratively-Built Knowledge Sources and AI. [pdf] [bibtex]

2009

  1. Jonathan Gordon, Benjamin Van Durme, and Lenhart K. Schubert. 2009. Weblogs as a source for extracting general world knowledge. In K-CAP ’09. [pdf] [bibtex]
  2. Benjamin Van Durme and Ashwin Lall. 2009. Probabilistic Counting with Randomized Storage. In IJCAI. [pdf] [bibtex]
  3. Benjamin Van Durme and D. Gildea. 2009. Topic Models for Corpus-centric Knowledge Generalization. In Technical Report TR-946, Department of Computer Science, University of Rochester. [pdf] [bibtex]
  4. Ting Qian, Benjamin Van Durme, and Lenhart Schubert. 2009. Building a Semantic Lexicon of English Nouns via Bootstrapping. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium, pages 37–42, Boulder, Colorado. Association for Computational Linguistics. [pdf] [bibtex]
  5. Benjamin Van Durme, Phillip Michalak, and Lenhart Schubert. 2009. Deriving Generalized Knowledge from Corpora Using WordNet Abstraction. In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009), pages 808–816, Athens, Greece. Association for Computational Linguistics. [pdf] [bibtex]
  6. Benjamin Van Durme and Ashwin Lall. 2009. Streaming Pointwise Mutual Information. In Yoshua Bengio, Dale Schuurmans, John D. Lafferty, Christopher K. I. Williams, and Aron Culotta, editors, Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, Vancouver, British Columbia, Canada, pages 1892–1900. Curran Associates, Inc. [pdf] [bibtex]
  7. Benjamin Van Durme and Ashwin Lall. 2009. Probabilistic Counting as an Extension to Randomized Count Storage. In Technical Report 942, Department of Computer Science, University of Rochester. [pdf] [bibtex]

2008

  1. Benjamin Van Durme, Ting Qian, and Lenhart Schubert. 2008. Class-Driven Attribute Extraction. In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008), pages 921–928, Manchester, UK. Coling 2008 Organizing Committee. [pdf] [bibtex]
  2. Benjamin Van Durme and Marius Pasca. 2008. Finding Cars, Goddesses and Enzymes: Parametrizable Acquisition of Labeled Instances for Open-Domain Information Extraction. In AAAI. [pdf] [bibtex]
  3. Dekang Lin, Shaojun Zhao, Benjamin Van Durme, and Marius Paşca. 2008. Mining Parenthetical Translations from the Web by Word Alignment. In Proceedings of ACL-08: HLT, pages 994–1002, Columbus, Ohio. Association for Computational Linguistics. [pdf] [bibtex]
  4. Marius Paşca and Benjamin Van Durme. 2008. Weakly-Supervised Acquisition of Open-Domain Classes and Class Attributes from Web Documents and Query Logs. In Proceedings of ACL-08: HLT, pages 19–27, Columbus, Ohio. Association for Computational Linguistics. [pdf] [bibtex]
  5. Benjamin Van Durme and Lenhart Schubert. 2008. Open Knowledge Extraction through Compositional Language Processing. In Semantics in Text Processing. STEP 2008 Conference Proceedings, pages 239–254. College Publications. [pdf] [bibtex]
  6. Benjamin Van Durme, Phillip Michalak, and Lenhart K. Schubert. 2008. Deriving Generic Statements using Corpus Acquired Knowledge and WordNet. In Technical Report 940, Department of Computer Science, University of Rochester. [pdf] [bibtex]
  7. Benjamin Van Durme, Phillip Michalak, and Lenhart K. Schubert. 2008. Notes on the Acquisition of Conditional Knowledge. In Technical Report 937, Department of Computer Science, University of Rochester. [pdf] [bibtex]

2007

  1. Marius Pasca, Benjamin Van Durme, and Nikesh Garera. 2007. The role of documents vs. queries in extracting class attributes from text. In CIKM ’07. [pdf] [bibtex]
  2. Marius Pasca and Benjamin Van Durme. 2007. What You Seek Is What You Get: Extraction of Class Attributes from Query Logs. In IJCAI. [pdf] [bibtex]

2005

  1. Kevin Knight, Hwee Tou Ng, and Kemal Oflazer, editors. 2005. Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05). Association for Computational Linguistics, Ann Arbor, Michigan. [pdf] [bibtex]

2004

  1. Anna Kupść, Teruko Mitamura, Benjamin Van Durme, and Eric Nyberg. 2004. Pronominal Anaphora Resolution for Unrestricted Text. In Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04), Lisbon, Portugal. European Language Resources Association (ELRA). [pdf] [bibtex]

2003

  1. Eric Nyberg, T. Mitamura, Jamie Callan, J. Carbonell, Robert E. Frederking, K. Collins-Thompson, Laurie Hiyakumoto, Yifen Huang, C. Huttenhower, S. Judy, Jeongwoo Ko, Anna Kupsc, L. Lita, V. Pedro, David Svoboda, and Benjamin Van Durme. 2003. The JAVELIN Question-Answering System at TREC 2003: A Multi-Strategh Approach with Dynamic Planning. In TREC. [pdf] [bibtex]
  2. Benjamin Van Durme, Yifen Huang, Anna Kupść, and Eric Nyberg. 2003. Towards light semantic processing for question answering. In Proceedings of the HLT-NAACL 2003 Workshop on Text Meaning, pages 54–61. [pdf] [bibtex]