Richard Futrell

About

Richard Futrell is an Associate Professor in the UC Irvine Department of Language Science where he leads the Language Processing Group. His research focuses on studying language processing in humans and machines through the application of information theory and Bayesian cognitive modeling. He also works on natural language processing (NLP) and AI interpretability, contributing to understanding the computational principles underlying language comprehension, production, and structure. His work explores how linguistic structures and processing efficiency are shaped by cognitive constraints and information-theoretic principles, often employing computational models to analyze language phenomena across different languages and modalities. Futrell's research has been recognized with awards such as the ACL Best Paper Award and the Best Paper Award for Computational Modeling of Language, reflecting his significant contributions to cognitive science and computational linguistics.

Research topics

• Natural Language Processing
• Artificial Intelligence
• Computer Science
• Linguistics
• Programming language
• Mathematics
• Cognitive psychology
• Psychology

Selected publications

• Lossy‐Context Surprisal: An Information‐Theoretic Model of Memory Effects in Sentence Processing

  Cognitive Science · 2020 · 156 citations

  1st authorCorresponding

  A key component of research on human sentence processing is to characterize the processing difficulty associated with the comprehension of words in context. Models that explain and predict this difficulty can be broadly divided into two kinds, expectation-based and memory-based. In this work, we present a new model of incremental sentence processing difficulty that unifies and extends key features of both kinds of models. Our model, lossy-context surprisal, holds that the processing difficulty a…

  DOI

• Composition is the Core Driver of the Language-selective Network

  Neurobiology of Language · 2020 · 113 citations

  = 47) by introducing a varying number of local word swaps into naturalistic sentences, leading to progressively less syntactically well-formed strings. Critically, local dependency relationships were preserved because combinable words remained close to each other. As predicted, word order degradation did not decrease the magnitude of the blood oxygen level-dependent response in the language network, except when combinable words were so far apart that composition among nearby words was highly unl…

  DOI

• Universals of word order reflect optimization of grammars for efficient communication

  Proceedings of the National Academy of Sciences · 2020 · 75 citations

  Senior authorCorresponding

  The universal properties of human languages have been the subject of intense study across the language sciences. We report computational and corpus evidence for the hypothesis that a prominent subset of these universal properties-those related to word order-result from a process of optimization for efficient communication among humans, trading off the need to reduce complexity with the need to reduce ambiguity. We formalize these two pressures with information-theoretic and neural-network models…

  DOI

• Mission: Impossible Language Models

  2024-01-01 · 16 citations

  articleOpen access

  Julie Kallini, Isabel Papadimitriou, Richard Futrell, Kyle Mahowald, Christopher Potts. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2024.

  PublisherOA PDFDOI

• Grammatical cues to subjecthood are redundant in a majority of simple clauses across languages

  Cognition · 2023-09-13 · 14 citations

  articleSenior author
  PublisherDOI

Recent grants

• CRII: RI: Opening the black box of neural natural language processing models using machine-behavioral methods

  NSF · $173k · 2020–2023

Frequent coauthors

• Roger Lévy

  70 shared

• Edward Gibson

  68 shared

• Evelina Fedorenko

  Massachusetts Institute of Technology

  51 shared

• Kyle Mahowald

  30 shared

• Michael Hahn

  28 shared

• Ethan Wilcox

  24 shared

• Idan Blank

  23 shared

• Titus von der Malsburg

  University of Stuttgart

  18 shared

Labs

• Language Processing GroupPI

Awards & honors

• Winner of Best Paper Award for Computational Modeling of Lan…
• Winner of ACL Best Paper Award (2024)
• Winner of the Sayan Gul Award for Best Undergraduate Paper (…
• Best Paper Award for Computational Modeling of Language (202…

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