Publications

Kate McCurdy, Michael Hahn (2024). Lossy Context Surprisal Predicts Task-Dependent Patterns in Relative Clause Processing. Proceedings of the 28th Conference on Computational Natural Language Learning (CoNLL 2024).

Kate McCurdy, Paul Soulos, Paul Smolensky, Roland Fernandez, Jianfeng Gao (2024). Toward Compositional Behavior in Neural Models: A Survey of Current Views. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024).

Xinting Huang, Andy Yang, Satwik Bhattamishra, Yash Sarrof, Andreas Krebs, Hattie Zhou, Preetum Nakkiran, Michael Hahn (2024). A Formal Framework for Understanding Length Generalization in Transformers. arXiv preprint.

Michael Hahn, Mark Rofin (2024). Why are Sensitive Functions Hard for Transformers?. Proceedings of the 2024 Annual Conference of the Association for Computational Linguistics. 🏆 Best Paper Award.

Yash Sarrof, Yana Veitsman, Michael Hahn (2024). The Expressive Capacity of State Space Models: A Formal Language Perspective. Annual Conference on Neural Information Processing Systems (NeurIPS 2024, poster).

Satwik Bhattamishra, Michael Hahn, Phil Blunsom, Varun Kanade (2024). Separations in the Representational Capabilities of Transformers and Recurrent Architectures. Annual Conference on Neural Information Processing Systems (NeurIPS 2024).

Siyu Tao, Lucia Donatelli, Michael Hahn (2024). More frequent verbs are associated with more diverse valency frames: Efficient language design at the lexicon-grammar interface. Proceedings of the 2024 Annual Conference of the Association for Computational Linguistics..

Richard Futrell, Michael Hahn (2024). Linguistic Structure from a Bottleneck on Sequential Information Processing. arXiv preprint..

Xinting Huang, Madhur Panwar, Navin Goyal, Michael Hahn (2024). InversionView: A General-Purpose Method for Reading Information from Neural Activations. Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
Previously: Mechanistic Interpretability Workshop at ICML 2024 (oral) 🏆 Awarded Second Place Prize.

Michael Hahn, Xue-Xin Wei (2024). A unifying theory explains seemingly contradictory biases in perceptual estimation. Nature Neuroscience.

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Michael Hahn, Navin Goyal (2023). A theory of emergent in-context learning as implicit structure induction. arXiv Preprint.

Thomas Hikaru Clark, Clara Meister, Tiago Pimentel, Michael Hahn, Ryan Cotterell, Richard Futrell, Roger Levy (2023). A Cross-Linguistic Pressure for Uniform Information Density in Word Order. Transactions of the Association for Computational Linguistics.

Michael Hahn, Frank Keller (2023). Modeling task effects in human reading with neural network-based attention. Cognition.

Michael Hahn, Richard Futrell, Roger Levy, Edward Gibson (2022). A resource-rational model of human processing of recursive linguistic structure. Proceedings of the National Academy of Sciences of the United States of America.

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Michael Hahn, Yang Xu (2022). Crosslinguistic word order variation reflects evolutionary pressures of dependency and information locality. Proceedings of the National Academy of Sciences of the United States of America.

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Michael Hahn, Rebecca Mathew, Judith Degen (2022). Morpheme ordering across languages reflects optimization for processing efficiency. Open Mind: Discoveries in Cognitive Science.

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Songpeng Yan, Michael Hahn, Frank Keller (2022). Modeling fixation behavior in reading with character-level neural attention. Proceedings of the 44th Annual Meeting of the Cognitive Science Society (CogSci).

Neil Rathi, Michael Hahn, Richard Futrell (2022). Explaining patterns of fusion in morphological paradigms using the memory--surprisal tradeoff. Proceedings of the 44th Annual Meeting of the Cognitive Science Society (CogSci).

Richard Futrell, Michael Hahn (2022). Information theory as a bridge between language function and language form. Frontiers in Communication.

Michael Hahn, Judith Degen, Richard Futrell (2021). Modeling word and morpheme order in natural language as an efficient tradeoff of memory and surprisal. Psychological Review.

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Michael Hahn, Dan Jurafsky, Richard Futrell (2021). Sensitivity as a complexity measure for sequence classification tasks. Transactions of the Association for Computational Linguistics.

Neil Rathi, Michael Hahn, Richard Futrell (2021). An Information-Theoretic Characterization of Morphological Fusion. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

Michael Hahn, Dan Jurafsky, Richard Futrell (2020). Universals of word order reflect optimization of grammars for efficient communication. Proceedings of the National Academy of Sciences of the United States of America.

John Hewitt, Michael Hahn, Surya Ganguli, Percy Liang, Christopher Manning (2020). RNNs can generate bounded hierarchical languages with optimal memory. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020).

Michael Hahn, Marco Baroni (2019). Tabula nearly rasa: Probing the linguistic knowledge of character-level neural language models trained on unsegmented text. Transactions of the Association for Computational Linguistics.

Michael Hahn, Richard Futrell (2019). Estimating predictive rate-distortion curves via neural variational inference . Entropy.

Michael Hahn, Frank Keller, Yonatan Bisk, Yonatan Belinkov (2019). Character-based surprisal as a model of human reading in the presence of errors. Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci).

Michael Hahn, Andreas Krebs, Howard Straubing (2018). Wreath Products of Distributive Forest Algebras. Logic in Computer Science (LICS).

Michael Hahn, Judith Degen, Noah Goodman, Dan Jurafsky, Richard Futrell (2018). An information-theoretic explanation of adjective ordering preferences. Proceedings of the 40th Annual Meeting of the Cognitive Science Society (CogSci).

Michael Hahn, Frank Keller (2016). Modeling human reading with neural attention. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing.

Michael Hahn, Andreas Krebs, Klaus-Jörn Lange, Michael Ludwig (2015). Visibly Counter Languages and the Structure of NC1. Proceedings of Mathematical Foundations of Computer Science (MFCS) 2015.

Michael Hahn, Frank Richter (2015). Henkin Semantics for Reasoning with Natural Language. Journal of Language Modeling.

Michael Hahn (2014). Predication and NP Structure in an Omnipredicative Language: The Case of Khoekhoe. Proceedings of the 21st International Conference on Head-Driven Phrase Structure Grammar.

Michael Hahn, Detmar Meurers (2014). On deriving semantic representations from dependencies: A practical approach for evaluating meaning in learner corpora. Dependency Theory.

Michael Hahn (2013). Word Order Variation in Khoekhoe. Proceedings of the 20th International Conference on Head-Driven Phrase Structure Grammar.

Niels Ott, Ramon Ziai, Michael Hahn, Detmar Meurers (2013). CoMeT: Integrating different levels of linguistic modeling for meaning assessment. Proceedings of the 7th International Workshop on Semantic Evaluation (SemEval).

Michael Hahn, Detmar Meurers (2012). Evaluating the Meaning of Answers to Reading Comprehension Questions: A Semantics-Based Approach. Proceedings of the 7th Workshop on Innovative Use of NLP for Building Educational Applications (BEA7).

Michael Hahn (2012). Arabic Relativization Patterns: A Unified HPSG Analysis. Proceedings of the 19th International Conference on Head-Driven Phrase Structure Grammar.

Michael Hahn, Detmar Meurers (2011). On deriving semantic representations from dependencies: A practical approach for evaluating meaning in learner corpora. Proceedings of the Int. Conference on Dependency Linguistics (Depling 2011).

Michael Hahn (2011). Null Conjuncts and Bound Pronouns in Arabic. The Proceedings of the 18th International Conference on Head-Driven Phrase Structure Grammar.