Publications

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2026

Why Human Guidance Matters in Collaborative Vibe Coding
Haoyu Hu, Raja Marjieh, Katherine M Collins, Chenyi Li, Thomas L Griffiths, Ilia Sucholutsky, Nori Jacoby
arXiv preprint arXiv:2602.10473
AI Thought Partners

Under the Influence: Quantifying Persuasion and Vigilance in Large Language Models
Sasha Robinson, Kerem Oktar, Katherine M Collins, Ilia Sucholutsky, Kelsey R Allen
arXiv preprint arXiv:2602.21262
Large Language Models

Language Model Teams as Distributed Systems
Elizabeth Mieczkowski, Katherine M Collins, Ilia Sucholutsky, Natalia Vélez, Thomas L Griffiths
arXiv preprint arXiv:2603.12229
Large Language Models

Human-AI Synergy Supports Collective Creative Search
Chenyi Li, Raja Marjieh, Haoyu Hu, Mark Steyvers, Katherine M Collins, Ilia Sucholutsky, Nori Jacoby
arXiv preprint arXiv:2602.10001
AI Thought Partners

2025

When should we orchestrate multiple agents?
Umang Bhatt, Sanyam Kapoor, Mihir Upadhyay, Ilia Sucholutsky, Francesco Quinzan, Katherine M Collins, Adrian Weller, Andrew Gordon Wilson, Muhammad Bilal Zafar
arXiv preprint arXiv:2503.13577
AI Thought Partners

What is a Number, That a Large Language Model May Know It?
Raja Marjieh, Veniamin Veselovsky, Thomas L Griffiths, Ilia Sucholutsky
arXiv preprint arXiv:2502.01540
Large Language Models

Using the tools of cognitive science to understand large language models at different levels of analysis
Alexander Ku, Declan Campbell, Xuechunzi Bai, Jiayi Geng, Ryan Liu, Raja Marjieh, R Thomas McCoy, Andrew Nam, Ilia Sucholutsky, Veniamin Veselovsky, Liyi Zhang, Jian-Qiao Zhu, Thomas L Griffiths
arXiv e-prints
Large Language ModelsCognitive Science

Using LLMs to advance the cognitive science of collectives
Ilia Sucholutsky, Katherine M Collins, Nori Jacoby, Bill D Thompson, Robert D Hawkins
Nature Computational Science
Large Language ModelsCognitive Science

Revisiting Rogers' Paradox in the Context of Human-AI Interaction
Katherine M Collins, Umang Bhatt, Ilia Sucholutsky
arXiv preprint arXiv:2501.10476
AI Thought Partners

Representational Alignment Supports Effective Teaching
Ilia Sucholutsky, Katherine M Collins, Maya Malaviya, Nori Jacoby, Weiyang Liu, Theodore Sumers, Michalis Korakakis, Umang Bhatt, Mark K Ho, Joshua B Tenenbaum, Bradley C Love, Zachary Pardos, Adrian Weller, Thomas L Griffiths
ICLR 2025 Workshop on Bidirectional Human-AI Alignment
Representational Alignment

On benchmarking human-like intelligence in machines
Lance Ying, Katherine M Collins, Lionel Wong, Ilia Sucholutsky, Ryan Liu, Adrian Weller, Tianmin Shu, Thomas L Griffiths, Joshua B Tenenbaum
arXiv preprint arXiv:2502.20502
Cognitive Science

Measuring and mitigating overreliance is necessary for building human-compatible AI
Lujain Ibrahim, Katherine M Collins, Sunnie SY Kim, Anka Reuel, Max Lamparth, Kevin Feng, Lama Ahmad, Prajna Soni, Alia El Kattan, Merlin Stein, Siddharth Swaroop, Ilia Sucholutsky, Andrew Strait, Q Vera Liao, Umang Bhatt
arXiv preprint arXiv:2509.08010
AI Thought Partners

Learning a Doubly-Exponential Number of Concepts From Few Examples
Ilia Sucholutsky, Bonan Zhao, Hee Seung Hwang, Allison Chen, Olga Russakovsky, Tom Griffiths
Proceedings of the Annual Meeting of the Cognitive Science Society
Few-Shot Learning

Large language models surpass human experts in predicting neuroscience results
Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun, Kevin K Nejad, Felipe Yáñez, Bati Yilmaz, Kangjoo Lee, Alexandra O Cohen, Valentina Borghesani, Anton Pashkov, Daniele Marinazzo, Jonathan Nicholas, Alessandro Salatiello, Ilia Sucholutsky, Pasquale Minervini, Sepehr Razavi, Roberta Rocca, Elkhan Yusifov, Tereza Okalova, Nianlong Gu, Martin Ferianc, Mikail Khona, Kaustubh R Patil, Pui-Shee Lee, Rui Mata, Nicholas E Myers, Jennifer K Bizley, Sebastian Musslick, Isil Poyraz Bilgin, Guiomar Niso, Justin M Ales, Michael Gaebler, N Apurva Ratan Murty, Leyla Loued-Khenissi, Anna Behler, Chloe M Hall, Jessica Dafflon, Sherry Dongqi Bao, Bradley C Love
Nature human behaviour
Large Language ModelsCognitive Science

Identifying, Evaluating, and Mitigating Risks of AI Thought Partnerships
Kerem Oktar, Katherine M Collins, Jose Hernandez-Orallo, Diane Coyle, Stephen Cave, Adrian Weller, Ilia Sucholutsky
arXiv preprint arXiv:2505.16899
AI Thought Partners

Humanity's last exam
Long Phan, Alice Gatti, Ziwen Han, Nathaniel Li, Josephina Hu, Hugh Zhang, Chen Bo Calvin Zhang, Mohamed Shaaban, John Ling, Sean Shi, Michael Choi, Anish Agrawal, Arnav Chopra, Adam Khoja, Ryan Kim, Richard Ren, Jason Hausenloy, Oliver Zhang, Mantas Mazeika, Dmitry Dodonov, Tung Nguyen, Jaeho Lee, Daron Anderson, Mikhail Doroshenko, Alun Cennyth Stokes, Mobeen Mahmood, Oleksandr Pokutnyi, Oleg Iskra, Jessica P Wang, John-Clark Levin, Mstyslav Kazakov, Fiona Feng, Steven Y Feng, Haoran Zhao, Michael Yu, Varun Gangal, Chelsea Zou, Zihan Wang, Serguei Popov, Robert Gerbicz, Geoff Galgon, Johannes Schmitt, Will Yeadon, Yongki Lee, Scott Sauers, Alvaro Sanchez, Fabian Giska, Marc Roth, Søren Riis, Saiteja Utpala, Noah Burns, Gashaw M Goshu, Mohinder Maheshbhai Naiya, Chidozie Agu, Zachary Giboney, Antrell Cheatom, Francesco Fournier-Facio, Sarah-Jane Crowson, Lennart Finke, Zerui Cheng, Jennifer Zampese, Ryan G Hoerr, Mark Nandor, Hyunwoo Park, Tim Gehrunger, Jiaqi Cai, Ben McCarty, Alexis C Garretson, Edwin Taylor, Damien Sileo, Qiuyu Ren, Usman Qazi, Lianghui Li, Jungbae Nam, John B Wydallis, Pavel Arkhipov, Jack Wei Lun Shi, Aras Bacho, Chris G Willcocks, Hangrui Cao, Sumeet Motwani, Emily de Oliveira Santos, Johannes Veith, Edward Vendrow, Doru Cojoc, Kengo Zenitani, Joshua Robinson, Longke Tang, Yuqi Li, Joshua Vendrow, Natanael Wildner Fraga, Vladyslav Kuchkin, Andrey Pupasov Maksimov, Pierre Marion, Denis Efremov, Jayson Lynch, Kaiqu Liang, Aleksandar Mikov, Andrew Gritsevskiy, Julien Guillod, Gözdenur Demir, Dakotah Martinez, Ben Pageler, Kevin Zhou, Saeed Soori, Ori Press, Henry Tang, Paolo Rissone, Sean R Green, Lina Brüssel, Moon Twayana, Aymeric Dieuleveut, Joseph Marvin Imperial, Ameya Prabhu, Jinzhou Yang, Nick Crispino, Arun Rao, Dimitri Zvonkine, Gabriel Loiseau, Mikhail Kalinin, Marco Lukas, Ciprian Manolescu, Nate Stambaugh, Subrata Mishra, Tad Hogg, Carlo Bosio, Brian P Coppola, Julian Salazar, Jaehyeok Jin, Rafael Sayous, Stefan Ivanov, Philippe Schwaller, Shaipranesh Senthilkuma, Andres M Bran, Andres Algaba, Kelsey Van den Houte, Lynn Van Der Sypt, Brecht Verbeken, David Noever, Alexei Kopylov, Benjamin Myklebust, Bikun Li, Lisa Schut, Evgenii Zheltonozhskii, Qiaochu Yuan, Derek Lim, Richard Stanley, Tong Yang, John Maar, Julian Wykowski
arXiv preprint arXiv:2501.14249

Explicitly unbiased large language models still form biased associations
Xuechunzi Bai, Angelina Wang, Ilia Sucholutsky, Thomas L Griffiths
Proceedings of the National Academy of Sciences
Large Language Models

Characterizing the Large‐Scale Structure of Multimodal Semantic Networks
Raja Marjieh, Pol van Rijn, Ilia Sucholutsky, Harin Lee, Nori Jacoby, Thomas L Griffiths
Cognitive science
Cognitive Science

AI Impact on Human Proof Formalization Workflows
Katherine M Collins, Simon Frieder, Jonas Bayer, Jacob Loader, Jeck Lim, Peiyang Song, Fabian Zaiser, Lexin Zhou, Shanda Li, Shi-Zhuo Looi, Jose Hernandez-Orallo, Joshua B Tenenbaum, Cameron Freer, Umang Bhatt, Adrian Weller, Valerie Chen, Ilia Sucholutsky
The 5th Workshop on Mathematical Reasoning and AI at NeurIPS 2025
Human-AI Interaction

2024

exKidneyBERT: a language model for kidney transplant pathology reports and the crucial role of extended vocabularies
Tiancheng Yang, Ilia Sucholutsky, Kuang-Yu Jen, Matthias Schonlau
PeerJ Computer Science
Large Language Models

Why should we care if machines learn human-like representations?
Ilia Sucholutsky, Thomas L Griffiths
AAAI-24 Spring Symposium on Human-Like Learning
Representational Alignment

Using compositionality to learn many categories from few examples
Ilia Sucholutsky, Bonan Zhao, Tom Griffiths
Proceedings of the Annual Meeting of the Cognitive Science Society
Few-Shot Learning

Towards formalizing spuriousness of biased datasets using partial information decomposition
Barproda Halder, Faisal Hamman, Pasan Dissanayake, Qiuyi Zhang, Ilia Sucholutsky, Sanghamitra Dutta
arXiv preprint arXiv:2407.00482
Dataset Distillation

Studying the Effect of Globalization on Color Perception using Multilingual Online Recruitment and Large Language Models
Jakob Niedermann, Ilia Sucholutsky, Raja Marjieh, Elif Celen, Thomas L Griffiths, Nori Jacoby, Pol van Rijn
Large Language ModelsCognitive Science

Quantifying spuriousness of biased datasets using partial information decomposition
Barproda Halder, Faisal Hamman, Pasan Dissanayake, Qiuyi Zhang, Ilia Sucholutsky, Sanghamitra Dutta
arXiv e-prints
Dataset Distillation

Quantifying knowledge distillation using partial information decomposition
Pasan Dissanayake, Faisal Hamman, Barproda Halder, Ilia Sucholutsky, Qiuyi Zhang, Sanghamitra Dutta
arXiv preprint arXiv:2411.07483
Dataset Distillation

Pushing the Limits of Learning from Limited Data
Maya Malaviya, Ilia Sucholutsky, Thomas L Griffiths
Proceedings of the AAAI Symposium Series
Few-Shot Learning

Preference-conditioned language-guided abstraction
Andi Peng, Andreea Bobu, Belinda Z Li, Theodore R Sumers, Ilia Sucholutsky, Nishanth Kumar, Thomas L Griffiths, Julie A Shah

Multilevel interpretability of artificial neural networks: leveraging framework and methods from neuroscience
Zhonghao He, Jascha Achterberg, Katie Collins, Kevin Nejad, Danyal Akarca, Yinzhu Yang, Wes Gurnee, Ilia Sucholutsky, Yuhan Tang, Rebeca Ianov, George Ogden, Chole Li, Kai Sandbrink, Stephen Casper, Anna Ivanova, Grace W Lindsay
arXiv preprint arXiv:2408.12664
Representational Alignment

Modulating language model experiences through frictions
Katherine M Collins, Valerie Chen, Ilia Sucholutsky, Hannah Rose Kirk, Malak Sadek, Holli Sargeant, Ameet Talwalkar, Adrian Weller, Umang Bhatt
arXiv preprint arXiv:2407.12804
Large Language ModelsHuman-AI Interaction

Mind your step (by step): Chain-of-thought can reduce performance on tasks where thinking makes humans worse
Ryan Liu, Jiayi Geng, Addison J Wu, Ilia Sucholutsky, Tania Lombrozo, Thomas L Griffiths
arXiv preprint arXiv:2410.21333
Large Language Models

Learning with language-guided state abstractions
Andi Peng, Ilia Sucholutsky, Belinda Z Li, Theodore R Sumers, Thomas L Griffiths, Jacob Andreas, Julie A Shah
arXiv preprint arXiv:2402.18759

Learning human-like representations to enable learning human values
Andrea Hui Wynn
Representational Alignment

Large language models predict human sensory judgments across six modalities
Raja Marjieh, Ilia Sucholutsky, Pol van Rijn, Nori Jacoby, Thomas L Griffiths
Scientific Reports
Large Language ModelsCognitive Science

Large language models assume people are more rational than we really are
Ryan Liu, Jiayi Geng, Joshua C Peterson, Ilia Sucholutsky, Thomas L Griffiths
arXiv preprint arXiv:2406.17055
Large Language ModelsCognitive Science

GPT is an effective tool for multilingual psychological text analysis
Steve Rathje, Dan-Mircea Mirea, Ilia Sucholutsky, Raja Marjieh, Claire E Robertson, Jay J Van Bavel
Proceedings of the National Academy of Sciences
Large Language Models

First Workshop on Representational Alignment (Re-Align)
Erin Grant, Ilia Sucholutsky, Jascha Achterberg, Katherine Hermann, Lukas Muttenthaler
ICLR 2024 Workshops
Representational Alignment

Dimensions of disagreement: Divergence and misalignment in cognitive science and artificial intelligence.
Kerem Oktar, Ilia Sucholutsky, Tania Lombrozo, Thomas L Griffiths
Decision
Representational AlignmentCognitive Science

Concept alignment
Sunayana Rane, Polyphony J Bruna, Ilia Sucholutsky, Christopher Kello, Thomas L Griffiths
arXiv preprint arXiv:2401.08672
Representational Alignment

Characterizing the Large-Scale Structure of Grounded Semantic Networks
Raja Marjieh, Pol van Rijn, Ilia Sucholutsky, Harin Lee, Nori Jacoby, Thomas L Griffiths
Cognitive Science

Characterizing similarities and divergences in conversational tones in humans and llms by sampling with people
Dun-Ming Huang, Pol Van Rijn, Ilia Sucholutsky, Raja Marjieh, Nori Jacoby
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Large Language ModelsHuman-AI Interaction

Building machines that learn and think with people
Katherine M Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E Zhang, Tan Zhi-Xuan, Mark Ho, Vikash Mansinghka, Adrian Weller, Joshua B Tenenbaum, Thomas L Griffiths
AI Thought Partners

Analyzing the roles of language and vision in learning from limited data
Allison Chen, Ilia Sucholutsky, Olga Russakovsky, Thomas L Griffiths
arXiv preprint arXiv:2403.19669
Few-Shot Learning

Adaptive language-guided abstraction from contrastive explanations
Andi Peng, Belinda Z Li, Ilia Sucholutsky, Nishanth Kumar, Julie A Shah, Jacob Andreas, Andreea Bobu
arXiv preprint arXiv:2409.08212

A rational analysis of the speech-to-song illusion
Raja Marjieh, Pol van Rijn, Ilia Sucholutsky, Harin Lee, Thomas L Griffiths, Nori Jacoby
arXiv preprint arXiv:2402.06992
Cognitive Science

2023

What language reveals about perception: Distilling psychophysical knowledge from large language models
Raja Marjieh, Ilia Sucholutsky, Pol van Rijn, Nori Jacoby, Tom Griffiths
Proceedings of the Annual Meeting of the Cognitive Science Society
Large Language ModelsCognitive Science

On the informativeness of supervision signals
Ilia Sucholutsky, Ruairidh M Battleday, Katherine M Collins, Raja Marjieh, Joshua Peterson, Pulkit Singh, Umang Bhatt, Nori Jacoby, Adrian Weller, Thomas L Griffiths
Uncertainty in Artificial Intelligence
Human-AI Interaction

Large language models meet cognitive science: LLMs as tools, models, and participants
Mathew Hardy, Ilia Sucholutsky, Bill Thompson, Tom Griffiths
Proceedings of the annual meeting of the cognitive science society
Large Language ModelsCognitive Science

Introducing deep learning and interpreting the patterns – a mineral deposit perspective
David First, Ilia Sucholutsky, Daniel Mogilny, Farzi Yusufali
Mineral Resource Estimation Conference 2023

Human uncertainty in concept-based ai systems
Katherine Maeve Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller, Krishnamurthy Dvijotham
Human-AI Interaction

Getting aligned on representational alignment
Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C Love, Erin Grant, Iris Groen, Jascha Achterberg, Joshua B Tenenbaum, Katherine M Collins, Katherine L Hermann, Kerem Oktar, Klaus Greff, Martin N Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P O'Connell, Thomas Unterthiner, Andrew K Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L Griffiths
arXiv preprint arXiv:2310.13018
Representational Alignment

End-to-End Learnable Masks With Differentiable Indexing
Dibyanshu Shekhar, Sree Harsha Nelaturu, Ashwath Shetty, Ilia Sucholutsky

Concept alignment as a prerequisite for value alignment
Sunayana Rane, Mark Ho, Ilia Sucholutsky, Thomas L Griffiths
arXiv preprint arXiv:2310.20059
Representational Alignment

Around the world in 60 words: A generative vocabulary test for online research
Pol van Rijn, Yue Sun, Harin Lee, Raja Marjieh, Ilia Sucholutsky, Francesca Lanzarini, Elisabeth André, Nori Jacoby
arXiv preprint arXiv:2302.01614

Alignment with human representations supports robust few-shot learning
Ilia Sucholutsky, Tom Griffiths
Advances in Neural Information Processing Systems
Representational AlignmentFew-Shot Learning

2022

Words are all you need? language as an approximation for human similarity judgments
Raja Marjieh, Pol Van Rijn, Ilia Sucholutsky, Theodore R Sumers, Harin Lee, Thomas L Griffiths, Nori Jacoby
arXiv preprint arXiv:2206.04105
Cognitive Science

Predicting human similarity judgments using large language models
Raja Marjieh, Ilia Sucholutsky, Theodore R Sumers, Nori Jacoby, Thomas L Griffiths
arXiv preprint arXiv:2202.04728
Large Language ModelsCognitive Science

Playing the Lottery of a Lifetime: The Effect of Socially Induced Aspiration on Q-Learning Agents
Yosi Hatekar, Rachit Dubey, Ted Sumers, Ilia Sucholutsky
Proceedings of the Annual Meeting of the Cognitive Science Society

Human-in-the-Loop Mixup
Katherine M Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Ilia Sucholutsky, Bradley Love, Adrian Weller
Uncertainty in Artificial Intelligence, 2023
Human-AI Interaction

Can humans do less-than-one-shot learning?
Maya Malaviya, Ilia Sucholutsky, Kerem Oktar, Thomas L Griffiths
arXiv preprint arXiv:2202.04670
Few-Shot Learning

Analyzing diffusion as serial reproduction
Raja Marjieh, Ilia Sucholutsky, Thomas A Langlois, Nori Jacoby, Thomas L Griffiths
arXiv preprint arXiv:2209.14821
Cognitive Science

2021

Secdd: Efficient and secure method for remotely training neural networks (student abstract)
Ilia Sucholutsky, Matthias Schonlau
Proceedings of the AAAI Conference on Artificial Intelligence

Optimal 1-NN prototypes for pathological geometries
Ilia Sucholutsky, Matthias Schonlau
PeerJ Computer Science
Few-Shot Learning

One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes
Ilia Sucholutsky, Nam-Hwui Kim, Ryan P Browne, Matthias Schonlau
2021 International Joint Conference on Neural Networks (IJCNN)
Few-Shot Learning

'Less Than One'-Shot Learning: Learning N Classes From M< N Samples
Ilia Sucholutsky, Matthias Schonlau
Proceedings of the AAAI Conference on Artificial Intelligence
Few-Shot Learning

Learning From Almost No Data
Ilia Sucholutsky
Few-Shot Learning

2019

Soft-Label Dataset Distillation and Text Dataset Distillation
Ilia Sucholutsky, Matthias Schonlau
2021 International Joint Conference on Neural Networks
Dataset Distillation

Pay attention and you won’t lose it: a deep learning approach to sequence imputation
Ilia Sucholutsky, Apurva Narayan, Matthias Schonlau, Sebastian Fischmeister
PeerJ Computer Science

Deep Learning for System Trace Restoration
Ilia Sucholutsky, Apurva Narayan, Matthias Schonlau, Sebastian Fischmeister
2019 International Joint Conference on Neural Networks (IJCNN)

2018

ConvART: Improving Adaptive Resonance Theory for Unsupervised Image Clustering
Ilia Sucholutsky, Matthias Schonlau
Journal of Computational Vision and Imaging Systems

2017

Text mining with n-gram variables
Matthias Schonlau, Nick Guenther, Ilia Sucholutsky
The Stata Journal