CLiMB Lab @ Stanford

Laboratory for Computation & Language in Minds & Brains

Welcome to the online home of the CLiMB Lab at Stanford! The grand goal of the lab is to solve human language comprehension. How do our brains go from sensation to meaning so effortlessly, and how do they learn this ability from experience? This simple goal presents immense challenges because understanding language requires understanding the different processes that shape it: learning, computation, and brain function. We therefore take an interdisciplinary approach that reflects this scope, recruiting trainees from many academic backgrounds (linguistics, computer science, psychology, cognitive science, and neuroscience) and building a culture where cross-disciplinary training and integrative research are the norm: linguists run neuroimaging experiments, computer scientists run human behavioral experiments, and neuroscientists study the functional organization of artificial intelligence (AI) models.

selected publications

EMNLP

Constructions are Revealed in Word Distributions

Rozner, Joshua, Weissweiler, Leonie, Mahowald, Kyle, and Shain, Cory

In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing Nov, 2025

SAC Highlight Award

Abs Bib HTML

Construction grammar posits that constructions, or form-meaning pairings, are acquired through experience with language (the distributional learning hypothesis).But how much information about constructions does this distribution actually contain? Corpus-based analyses provide some answers, but text alone cannot answer counterfactual questions about what caused a particular word to occur.This requires computable models of the distribution over strings—namely, pretrained language models (PLMs).Here, we treat a RoBERTa model as a proxy for this distribution and hypothesize that constructions will be revealed within it as patterns of statistical affinity.We support this hypothesis experimentally: many constructions are robustly distinguished, including (i) hard cases where semantically distinct constructions are superficially similar, as well as (ii) schematic constructions, whose “slots” can be filled by abstract word classes.Despite this success, we also provide qualitative evidence that statistical affinity alone may be insufficient to identify all constructions from text.Thus, statistical affinity is likely an important, but partial, signal available to learners.

@inproceedings{rozner-etal-2025-constructions,
  title = {Constructions are Revealed in Word Distributions},
  author = {Rozner, Joshua and Weissweiler, Leonie and Mahowald, Kyle and Shain, Cory},
  editor = {Christodoulopoulos, Christos and Chakraborty, Tanmoy and Rose, Carolyn and Peng, Violet},
  booktitle = {Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing},
  month = nov,
  year = {2025},
  address = {Suzhou, China},
  publisher = {Association for Computational Linguistics},
  doi = {10.18653/v1/2025.emnlp-main.108},
  pages = {2116--2138},
  isbn = {979-8-89176-332-6},
  award = {SAC Highlight Award}
}

JoCN

Distributed Sensitivity to Syntax and Semantics throughout the Language Network

Shain, Cory, Kean, Hope, Casto, Colton, Lipkin, Benjamin, Affourtit, Josef, Siegelman, Matthew, Mollica, Francis, and Fedorenko, Evelina

Journal of Cognitive Neuroscience Nov, 2024

Bib PDF

@article{shainetal24:nlength,
  author = {Shain, Cory and Kean, Hope and Casto, Colton and Lipkin, Benjamin and Affourtit, Josef and Siegelman, Matthew and Mollica, Francis and Fedorenko, Evelina},
  title = {Distributed Sensitivity to Syntax and Semantics throughout the Language Network},
  year = {2024},
  journal = {Journal of Cognitive Neuroscience},
  section = {articles},
}

PNAS

Large-scale evidence for logarithmic effects of word predictability on reading time

Shain, Cory, Meister, Clara, Pimentel, Tiago, Cotterell, Ryan, and Levy, Roger

Proceedings of the National Academy of Sciences Nov, 2024

Bib PDF

@article{shainetal24,
  author = {Shain, Cory and Meister, Clara and Pimentel, Tiago and Cotterell, Ryan and Levy, Roger},
  title = {Large-scale evidence for logarithmic effects of word predictability on reading time},
  year = {2024},
  doi = {https://doi.org/10.1073/pnas.2307876121},
  journal = {Proceedings of the National Academy of Sciences},
  volume = {121},
  number = {10},
  pages = {e2307876121},
  section = {articles},
}

Open Mind

Word Frequency and Predictability Dissociate in Naturalistic Reading

Shain, Cory

Open Mind: Discoveries in Cognitive Science Nov, 2024

Bib PDF

@article{shain24,
  author = {Shain, Cory},
  title = {Word Frequency and Predictability Dissociate in Naturalistic Reading},
  year = {2024},
  journal = {Open Mind: Discoveries in Cognitive Science},
  volume = {8},
  pages = {177--201},
  section = {articles},
}

Open Mind

A deep learning approach to analyzing continuous-time cognitive processes

Shain, Cory, and Schuler, William

Open Mind: Discoveries in Cognitive Science Nov, 2024

Bib PDF

@article{shainschuler24,
  author = {Shain, Cory and Schuler, William},
  title = {A deep learning approach to analyzing continuous-time cognitive processes},
  year = {2024},
  journal = {Open Mind: Discoveries in Cognitive Science},
  volume = {8},
  pages = {235--264},
  section = {articles},
}

Cer Cort

No evidence of theory of mind reasoning in the human language network

Shain, Cory, Paunov, Alexander, Chen, Xuanyi, Lipkin, Benjamin, and Fedorenko, Evelina

Cerebral Cortex Nov, 2023

Bib PDF

@article{shainetal23:tom,
  author = {Shain, Cory and Paunov, Alexander and Chen, Xuanyi and Lipkin, Benjamin and Fedorenko, Evelina},
  title = {No evidence of theory of mind reasoning in the human language network},
  year = {2023},
  journal = {Cerebral Cortex},
  number = {33},
  pages = {6299--6319},
  doi = {https://doi.org/10.1093/cercor/bhac505},
  section = {articles},
}

J Neuro

Robust effects of working memory demand during naturalistic language comprehension in language-selective cortex

Shain, Cory, Blank, Idan A., Fedorenko, Evelina, Gibson, Edward, and Schuler, William

Journal of Neuroscience Nov, 2022

Bib PDF

@article{shainetal22,
  author = {Shain, Cory and Blank, Idan A. and Fedorenko, Evelina and Gibson, Edward and Schuler, William},
  title = {Robust effects of working memory demand during naturalistic language comprehension in language-selective cortex},
  year = {2022},
  journal = {Journal of Neuroscience},
  volume = {42},
  issue = {39},
  pages = {7412--7430},
  doi = {https://doi.org/10.1523/JNEUROSCI.1894-21.2022},
  section = {articles},
}

Npsy

fMRI reveals language-specific predictive coding during naturalistic sentence comprehension

Shain, Cory, Blank, Idan, van Schijndel, Marten, Schuler, William, and Fedorenko, Evelina

Neuropsychologia Nov, 2020

Bib PDF Code

@article{shainetal20,
  title = {fMRI reveals language-specific predictive coding during naturalistic sentence comprehension},
  author = {Shain, Cory and Blank, Idan and {van Schijndel}, Marten and Schuler, William and Fedorenko, Evelina},
  year = {2020},
  journal = {Neuropsychologia},
  volume = {138},
  pages = {107307},
  doi = {10.1101/717512},
  section = {articles},
  data = {https://osf.io/eyp8q/},
  project = {cdrnn,mempred},
}