Michael Hahn

Michael Hahn

Stanford University

H-index: 13

North America-United States

About Michael Hahn

Michael Hahn, With an exceptional h-index of 13 and a recent h-index of 12 (since 2020), a distinguished researcher at Stanford University,

His recent articles reflect a diverse array of research interests and contributions to the field:

Why are Sensitive Functions Hard for Transformers?

A unifying theory explains seemingly contradictory biases in perceptual estimation

A theory of emergent in-context learning as implicit structure induction

How do syntactic statistics and semantic plausibility modulate local coherence effects

A Cross-Linguistic Pressure for Uniform Information Density in Word Order

Computational and Communicative Efficiency in Language

Modeling fixation behavior in reading with character-level neural attention

Explaining patterns of fusion in morphological paradigms using the memory--surprisal tradeoff

Michael Hahn Information

University

Position

___

Citations(all)

728

Citations(since 2020)

642

Cited By

241

hIndex(all)

13

hIndex(since 2020)

12

i10Index(all)

14

i10Index(since 2020)

13

Email

University Profile Page

Stanford University

Google Scholar

View Google Scholar Profile

Top articles of Michael Hahn

Title

Journal

Author(s)

Publication Date

Why are Sensitive Functions Hard for Transformers?

arXiv preprint arXiv:2402.09963

Michael Hahn

Mark Rofin

2024/2/15

A unifying theory explains seemingly contradictory biases in perceptual estimation

Nature Neuroscience

Michael Hahn

Xue-Xin Wei

2024/2/15

A theory of emergent in-context learning as implicit structure induction

arXiv preprint arXiv:2303.07971

Michael Hahn

Navin Goyal

2023/3/14

How do syntactic statistics and semantic plausibility modulate local coherence effects

Proceedings of the Annual Meeting of the Cognitive Science Society

Hailin Hao

Michael Hahn

Elsi Kaiser

2023

A Cross-Linguistic Pressure for Uniform Information Density in Word Order

Transactions of the Association for Computational Linguistics

Thomas Hikaru Clark

Clara Meister

Tiago Pimentel

Michael Hahn

Ryan Cotterell

...

2023/8/15

Computational and Communicative Efficiency in Language

Michael Hermann Hahn

2022

Modeling fixation behavior in reading with character-level neural attention

Proceedings of the Annual Meeting of the Cognitive Science Society

Songpeng Yan

Michael Hahn

Frank Keller

2022

Explaining patterns of fusion in morphological paradigms using the memory--surprisal tradeoff

Proceedings of the annual meeting of the cognitive science society

Neil Rathi

Michael Hahn

Richard Futrell

2022

A resource-rational model of human processing of recursive linguistic structure

Proceedings of the National Academy of Sciences

Michael Hahn

Richard Futrell

Roger Levy

Edward Gibson

2022/10/25

Crosslinguistic word order variation reflects evolutionary pressures of dependency and information locality

Proceedings of the National Academy of Sciences

Michael Hahn

Yang Xu

2022/6/14

Information theory as a bridge between language function and language form

Richard Futrell

Michael Hahn

2022/5/11

Sensitivity as a complexity measure for sequence classification tasks

Transactions of the Association for Computational Linguistics

Michael Hahn

Dan Jurafsky

Richard Futrell

2021/8/18

Modeling word and morpheme order in natural language as an efficient trade-off of memory and surprisal.

Psychological Review

Michael Hahn

Judith Degen

Richard Futrell

2021/7

An information-theoretic characterization of morphological fusion

An Information-Theoretic Characterization of Morphological Fusion

Neil Rathi

Michael Hahn

Richard Futrell

2021/1

Morpheme ordering across languages reflects optimization for processing efficiency

Open Mind

Michael Hahn

Rebecca Mathew

Judith Degen

2021/12/9

Supplementary Information: Morpheme Ordering across Languages Reflects Optimization for Processing Efficiency

Michael Hahn

Rebecca Mathew

Judith Degen

2021/11/18

Crosslinguistic Word Orders Enable an Efficient Tradeoff of Memory and Surprisal

Society for Computation in Linguistics

Michael Hahn

Richard Futrell

2020/1/1

Theoretical limitations of self-attention in neural sequence models

Transactions of the Association for Computational Linguistics

Michael Hahn

2020/1/1

RNNs can generate bounded hierarchical languages with optimal memory

arXiv preprint arXiv:2010.07515

John Hewitt

Michael Hahn

Surya Ganguli

Percy Liang

Christopher D Manning

2020/10/15

Supplementary Information for: Modeling word and morpheme order in natural language as an efficient tradeoff of memory and surprisal

Michael Hahn

Judith Degen

Richard Futrell

2020/9/15

See List of Professors in Michael Hahn University(Stanford University)