On deriving semantic representations from dependencies: A Practical approach for evaluating meaning in learner corpora. - Michael Hahn 001; Detmar Meurers (DepLing, 2011)

Evaluating the Meaning of Answers to Reading Comprehension Questions: A Semantics-Based Approach. - Michael Hahn 001; Detmar Meurers (BEA@NAACL-HLT, 2012)

CoMeT: Integrating different levels of linguistic modeling for meaning assessment. - Niels Ott; Ramon Ziai; Michael Hahn 001; Detmar Meurers (SemEval@NAACL-HLT, 2013)

Visibly Counter Languages and the Structure of NC1. - Michael Hahn 001; Andreas Krebs; Klaus-Jörn Lange; Michael Ludwig (MFCS (2), 2015)

Henkin semantics for reasoning with natural language. - Michael Hahn 001; Frank Richter 001 (J. Lang. Model., 2015)

Modeling Human Reading with Neural Attention. - Michael Hahn 001; Frank Keller (EMNLP, 2016)

An Information-Theoretic Explanation of Adjective Ordering Preferences. - Michael Hahn 001; Judith Degen; Noah D. Goodman; Dan Jurafsky; Richard Futrell (CogSci, 2018)

Wreath Products of Distributive Forest Algebras. - Michael Hahn 001; Andreas Krebs; Howard Straubing (LICS, 2018)

Modeling Task Effects in Human Reading with Neural Attention. - Michael Hahn 001; Frank Keller (CoRR, 2018)

Character-based Surprisal as a Model of Reading Difficulty in the Presence of Errors. - Michael Hahn 001; Frank Keller; Yonatan Bisk; Yonatan Belinkov (CogSci, 2019)

Character-based Surprisal as a Model of Human Reading in the Presence of Errors. - Michael Hahn 001; Frank Keller; Yonatan Bisk; Yonatan Belinkov (CoRR, 2019)

Estimating Predictive Rate-Distortion Curves via Neural Variational Inference. - Michael Hahn 001; Richard Futrell (Entropy, 2019)

Tabula nearly rasa: Probing the linguistic knowledge of character-level neural language models trained on unsegmented text. - Michael Hahn 001; Marco Baroni (Trans. Assoc. Comput. Linguistics, 2019)

RNNs can generate bounded hierarchical languages with optimal memory. - John Hewitt; Michael Hahn 001; Surya Ganguli; Percy Liang; Christopher D. Manning (EMNLP (1), 2020)

Theoretical Limitations of Self-Attention in Neural Sequence Models. - Michael Hahn 001 (Trans. Assoc. Comput. Linguistics, 2020)

An Information-Theoretic Characterization of Morphological Fusion. - Neil Rathi; Michael Hahn 001; Richard Futrell (EMNLP (1), 2021)

Sensitivity as a Complexity Measure for Sequence Classification Tasks. - Michael Hahn 001; Dan Jurafsky; Richard Futrell (Trans. Assoc. Comput. Linguistics, 2021)

Explaining patterns of fusion in morphological paradigms using the memory-surprisal tradeoff. - Neil Rathi; Michael Hahn 001; Richard Futrell (CogSci, 2022)

Modeling Fixation Behavior in Reading with Character-level Neural Attention. - Songpeng Yan; Michael Hahn 001; Frank Keller (CogSci, 2022)

Crosslinguistic word order variation reflects evolutionary pressures of dependency and information locality. - Michael Hahn 001; Yang Xu (CoRR, 2022)

How Do Syntactic Statistics and Semantic Plausibility Modulate Local Coherence Effects. - Hailin Hao; Michael Hahn 001; Elsi Kaiser (CogSci, 2023)

A Theory of Emergent In-Context Learning as Implicit Structure Induction. - Michael Hahn 001; Navin Goyal (CoRR, 2023)

A Cross-Linguistic Pressure for Uniform Information Density in Word Order. - Thomas Hikaru Clark; Clara Meister; Tiago Pimentel; Michael Hahn 001; Ryan Cotterell; Richard Futrell; Roger Levy (Trans. Assoc. Comput. Linguistics, 2023)

Why are Sensitive Functions Hard for Transformers? - Michael Hahn 001; Mark Rofin (ACL (1), 2024)

More frequent verbs are associated with more diverse valency frames: Efficient principles at the lexicon-grammar interface. - Siyu Tao; Lucia Donatelli; Michael Hahn 001 (ACL (1), 2024)

Separations in the Representational Capabilities of Transformers and Recurrent Architectures. - Satwik Bhattamishra; Michael Hahn 001; Phil Blunsom; Varun Kanade (NeurIPS, 2024)

InversionView: A General-Purpose Method for Reading Information from Neural Activations. - Xinting Huang; Madhur Panwar; Navin Goyal; Michael Hahn 001 (NeurIPS, 2024)

The Expressive Capacity of State Space Models: A Formal Language Perspective. - Yash Raj Sarrof; Yana Veitsman; Michael Hahn 001 (NeurIPS, 2024)

Linguistic Structure from a Bottleneck on Sequential Information Processing. - Richard Futrell; Michael Hahn 001 (CoRR, 2024)

A Formal Framework for Understanding Length Generalization in Transformers. - Xinting Huang; Andy Yang; Satwik Bhattamishra; Yash Raj Sarrof; Andreas Krebs; Hattie Zhou; Preetum Nakkiran; Michael Hahn 001 (ICLR, 2025)

Emergent Stack Representations in Modeling Counter Languages Using Transformers. - Utkarsh Tiwari; Aviral Gupta; Michael Hahn 001 (CoRR, 2025)

Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers. - Alireza Amiri; Xinting Huang; Mark Rofin; Michael Hahn 001 (CoRR, 2025)

Contextualize-then-Aggregate: Circuits for In-Context Learning in Gemma-2 2B. - Aleksandra Bakalova; Yana Veitsman; Xinting Huang; Michael Hahn 001 (CoRR, 2025)

Language models can learn implicit multi-hop reasoning, but only if they have lots of training data. - Yuekun Yao; Yupei Du; Dawei Zhu; Michael Hahn 001; Alexander Koller (CoRR, 2025)

Born a Transformer - Always a Transformer? - Yana Veitsman; Mayank Jobanputra; Yash Raj Sarrof; Aleksandra Bakalova; Vera Demberg; Ellie Pavlick; Michael Hahn 001 (CoRR, 2025)

Tug-of-war between idiom's figurative and literal meanings in LLMs. - Soyoung Oh; Xinting Huang; Mathis Pink; Michael Hahn 001; Vera Demberg (CoRR, 2025)

Position: Pause Recycling LoRAs and Prioritize Mechanisms to Uncover Limits and Effectiveness. - Mei-Yen Chen; Thi Thu Uyen Hoang; Michael Hahn 001; M. Saquib Sarfraz (CoRR, 2025)

Decomposing Representation Space into Interpretable Subspaces with Unsupervised Learning. - Xinting Huang; Michael Hahn 001 (CoRR, 2025)