Peter A Jansen

Interests

Teaching

Artificial Intelligence, Natural Language Processing, Rapid Prototyping

Research

Artificial Intelligence, Natural Language Processing, Automated Inference, Semantic Knowledge Representation, Question Answering, Explainable Inference, Cognitive Science

Courses

Scholarly Contributions

Journals/Publications

• Jansen, P. A., Sharp, R., Surdeanu, M., & Clark, P. (2017). Framing Question Answering as Building and Ranking Answer Justifications. Computational Linguistics, 40.
• Fried, D., Jansen, P., Hahn-Powell, G., Surdeanu, M., & Clark, P. (2015). Higher-order Lexical Semantic Models for Non-factoid Answer Reranking. Transactions of the Association for Computational Linguistics, 3, 197--210.

Proceedings Publications

• Jansen, P. (2020). CoSaTa: A Constraint Satisfaction Solver and Interpreted Language for Semi-Structured Tables of Sentences. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations.
• Jansen, P. (2020). Visually-Grounded Planning without Vision: Language Models Infer Detailed Plans from High-level Instructions. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings.
• Jansen, P., & Ustalov, D. (2020). TextGraphs 2020 Shared Task on Multi-Hop Inference for Explanation Regeneration. In Proceedings of the Graph-based Methods for Natural Language Processing (TextGraphs).
• Smith, H., Zhang, Z., Culnan, J., & Jansen, P. (2020). ScienceExamCER: A High-Density Fine-Grained Science-Domain Corpus for Common Entity Recognition. In Proceedings of The 12th Language Resources and Evaluation Conference.
• Xie, Z., Thiem, S., Martin, J., Wainwright, E., Marmorstein, S., & Jansen, P. (2020). Worldtree v2: A corpus of science-domain structured explanations and inference patterns supporting multi-hop inference. In Proceedings of The 12th Language Resources and Evaluation Conference.
• Xu, D., Jansen, P., Martin, J., Xie, Z., Yadav, V., Madabushi, H. T., Tafjord, O., & Clark, P. (2020). Multi-class Hierarchical Question Classification for Multiple Choice Science Exams. In Proceedings of The 12th Language Resources and Evaluation Conference.
• Jansen, P., & Ustalov, D. (2019). TextGraphs 2019 Shared Task on Multi-Hop Inference for Explanation Regeneration. In Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13).
• Khot, T., Clark, P., Guerquin, M., Jansen, P., & Sabharwal, A. (2020, Fall). QASC: A Dataset for Question Answering via Sentence Composition. In AAAI.
• Thiem, S., & Jansen, P. (2019). Extracting Common Inference Patterns from Semi-Structured Explanations. In Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing.
• Jansen, P. (2018). Multi-hop Inference for Sentence-level TextGraphs: How Challenging is Meaningfully Combining Information for Science Question Answering?. In Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-12).
• Jansen, P. A., Jansen, P. A., Wainwright, E., Wainwright, E., Marmorstein, S., Marmorstein, S., Morrison, C. T., & Morrison, C. T. (2018, May). WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-hop Inference. In Language Resources and Evaluation Conference (LREC).
• Kwan, H., Trivedi, H., Jansen, P. A., Surdeanu, M., & Balasubramanian, N. (2018, March). Controlling Information Aggregation for Complex Question Answering. In European Conference on Information Retrieval (ECIR).
• Jansen, P. A. (2017, December). A Study of Automatically Acquiring Explanatory Inference Patterns from Corpora of Explanations: Lessons from Elementary Science Exams. In The 2017 Workshop on Automatic Knowledge Base Construction (AKBC'2017).
• Sharp, R., Surdeanu, M., Jansen, P. A., Valenzuela-Escarcega, M., Clark, P., & Hammond, M. (2017, August). Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification. In SIGNLL Conference on Computational Natural Language Learning (CoNLL).
• Jansen, P., Balasubramanian, N., Surdeanu, M., & Clark, P. (2016, December). What's in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams. In Proceedings of the 26th International Conference on Computational Linguistics (COLING).
• Sharp, R., Surdeanu, M., Jansen, P., Clark, P., & Hammond, M. (2016, Fall). Creating Causal Embeddings for Question Answering with Minimal Supervision. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP).
• Sharp, R., Jansen, P., Surdeanu, M., & Clark, P. (2015, Spring). Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT).
• Jansen, P., Surdeanu, M., & Clark, P. (2014, Summer). Discourse Complements Lexical Semantics for Non-factoid Answer Reranking. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL).
• Forbes, A., Surdeanu, M., Jansen, P., & Carrington, J. (2013). Transmitting Narrative: An Interactive Shift-Summarization Tool for Improving Nurse Communication. In Proceedings of the 3rd IEEE Workshop on Interactive Visual Text Analytics.