Script Learning
An important part of understanding natural language is the incorporation of world knowledge. One possible way to encode world knowledge is in the form of scripts, which model stereotypical sequences of events. A script system learns scripts by generalizing such sequences of events from text. Recent work from our group in this area has explored new representations of events in scripts, and the use of recurrent neural networks to improve the learning of scripts.
Publications
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SAGEViz: SchemA GEneration and Visualization 2023
Sugam Devare, Mahnaz Koupaee, Gautham Gunapati, Sayontan Ghosh, Sai Vallurupalli, Yash Kumar Lal, Francis Ferraro, Nathanael Chambers, Greg Durrett, Raymond Mooney, Katrin Erk, Niranjan Balasubramanian, Empirical Methods in Natural Language Processing (EMNLP) Demo Track (2023).
Advances in Statistical Script Learning 2017
Karl Pichotta, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Learning Statistical Scripts with LSTM Recurrent Neural Networks 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, February 2016.
Statistical Script Learning with Recurrent Neural Networks 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the Workshop on Uphill Battles in Language Processing (UBLP) at EMNLP 2016, Austin, TX, November 2016.
Using Sentence-Level LSTM Language Models for Script Inference 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), pp. 279--289, Berlin, Germany 2016.
Statistical Script Learning with Recurrent Neural Nets 2015
Karl Pichotta, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Statistical Script Learning with Multi-Argument Events 2014
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2014), pp. 220--229, Gothenburg, Sweden, April 2014.
Schema acquisition from a single example 1992
W. Ahn, W. F. Brewer and Raymond J. Mooney, Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 18 (1992), pp. 391-412.
Learning Plan Schemata From Observation: Explanation-Based Learning for Plan Recognition 1990
Raymond J. Mooney, Cognitive Science, Vol. 14, 4 (1990), pp. 483-509.
Schema Acquisition from One Example: Psychological Evidence for Explanation-Based Learning 1987
W. Ahn, Raymond J. Mooney, W.F. Brewer and G.F. DeJong, In Proceedings of the Ninth Annual Conference of the Cognitive Science Society, pp. 50-57, Seattle, WA, July 1987.
Generalizing Explanations of Narratives into Schemata 1985
Raymond J. Mooney, Masters Thesis, Department of Computer Science, University of Illinois at Urbana-Champaign.
Generalizing Explanations of Narratives into Schemata 1985
Raymond J. Mooney, In Proceedings of the Third International Machine Learning Workshop, pp. 126--128, New Brunswick, New Jersey 1985.
Learning Schemata for Natural Language Processing 1985
Raymond J. Mooney and Gerald F. DeJong, In Proceedings of the Ninth International Joint Conference on Artificial Intelligence (IJCAI-85), pp. 681-687, Los Angeles, CA, August 1985.
Labs
Machine Learning