Deep Learning for System Trace Restoration. - Ilia Sucholutsky; Apurva Narayan; Matthias Schonlau; Sebastian Fischmeister (IJCNN, 2019)

Improving Dataset Distillation. - Ilia Sucholutsky; Matthias Schonlau (CoRR, 2019)

Pay attention and you won't lose it: a deep learning approach to sequence imputation. - Ilia Sucholutsky; Apurva Narayan; Matthias Schonlau; Sebastian Fischmeister (PeerJ Comput. Sci., 2019)

SecDD: Efficient and Secure Method for Remotely Training Neural Networks. - Ilia Sucholutsky; Matthias Schonlau (CoRR, 2020)

'Less Than One'-Shot Learning: Learning N Classes From M < N Samples. - Ilia Sucholutsky; Matthias Schonlau (AAAI, 2021)

SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract). - Ilia Sucholutsky; Matthias Schonlau (AAAI, 2021)

One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes. - Ilia Sucholutsky; Nam-Hwui Kim; Ryan P. Browne; Matthias Schonlau (IJCNN, 2021)

Soft-Label Dataset Distillation and Text Dataset Distillation. - Ilia Sucholutsky; Matthias Schonlau (IJCNN, 2021)

Optimal 1-NN prototypes for pathological geometries. - Ilia Sucholutsky; Matthias Schonlau (PeerJ Comput. Sci., 2021)

Learning From Almost No Data. - Ilia Sucholutsky (2021)

Playing the Lottery of a Lifetime: The Effect of Socially Induced Aspiration on Q-Learning Agents. - Yosi Hatekar; Rachit Dubey; Theodore R. Sumers; Ilia Sucholutsky (CogSci, 2022)

Can Humans Do Less-Than-One-Shot Learning? - Maya Malaviya; Ilia Sucholutsky; Kerem Oktar; Tom Griffiths 001 (CogSci, 2022)

Predicting Human Similarity Judgments Using Large Language Models. - Raja Marjieh; Ilia Sucholutsky; Theodore R. Sumers; Nori Jacoby; Tom Griffiths 001 (CogSci, 2022)

Words are all you need? Capturing human sensory similarity with textual descriptors. - Raja Marjieh; Pol van Rijn; Ilia Sucholutsky; Theodore R. Sumers; Harin Lee; Thomas L. Griffiths 001; Nori Jacoby (CoRR, 2022)

On the Informativeness of Supervision Signals. - Ilia Sucholutsky; Raja Marjieh; Nori Jacoby; Thomas L. Griffiths 001 (CoRR, 2022)

Human Uncertainty in Concept-Based AI Systems. - Katherine Maeve Collins; Matthew Barker; Mateo Espinosa Zarlenga; Naveen Raman 001; Umang Bhatt; Mateja Jamnik; Ilia Sucholutsky; Adrian Weller; Krishnamurthy Dvijotham (AIES, 2023)

Large language models meet cognitive science: LLMs as tools, models, and participants. - Mathew D. Hardy; Ilia Sucholutsky; Bill Thompson 001; Tom Griffiths 001 (CogSci, 2023)

What Language Reveals about Perception: Distilling Psychophysical Knowledge from Large Language Models. - Raja Marjieh; Ilia Sucholutsky; Pol van Rijn; Nori Jacoby; Tom Griffiths 001 (CogSci, 2023)

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 (CogSci, 2023)

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 001; Nori Jacoby (ICLR, 2023)

End-to-End Learnable Masks With Differentiable Indexing. - Dibyanshu Shekhar; Sree Harsha Nelaturu; Ashwath Shetty; Ilia Sucholutsky (Tiny Papers @ ICLR, 2023)

Analyzing Diffusion as Serial Reproduction. - Raja Marjieh; Ilia Sucholutsky; Thomas A. Langlois; Nori Jacoby; Thomas L. Griffiths 001 (ICML, 2023)

Alignment with human representations supports robust few-shot learning. - Ilia Sucholutsky; Tom Griffiths 001 (NeurIPS, 2023)

Human-in-the-Loop Mixup. - Katherine M. Collins; Umang Bhatt; Weiyang Liu; Vihari Piratla; Ilia Sucholutsky; Bradley C. Love; Adrian Weller (UAI, 2023)

On the informativeness of supervision signals. - Ilia Sucholutsky; Ruairidh M. Battleday; Katherine M. Collins; Raja Marjieh; Joshua C. Peterson; Pulkit Singh; Umang Bhatt; Nori Jacoby; Adrian Weller; Thomas L. Griffiths 001 (UAI, 2023)

Dimensions of Disagreement: Unpacking Divergence and Misalignment in Cognitive Science and Artificial Intelligence. - Kerem Oktar; Ilia Sucholutsky; Tania Lombrozo; Thomas L. Griffiths 001 (CoRR, 2023)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

Concept Alignment as a Prerequisite for Value Alignment. - Sunayana Rane; Mark K. Ho; Ilia Sucholutsky; Thomas L. Griffiths 001 (CoRR, 2023)

Pushing the Limits of Learning from Limited Data. - Maya Malaviya; Ilia Sucholutsky; Thomas L. Griffiths 001 (AAAI Spring Symposia, 2024)

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 (ACL (1), 2024)

Adaptive Language-Guided Abstraction from Contrastive Explanations. - Andi Peng; Belinda Z. Li; Ilia Sucholutsky; Nishanth Kumar; Julie Shah; Jacob Andreas; Andreea Bobu (CoRL, 2024)

Preference-Conditioned Language-Guided Abstraction. - Andi Peng; Andreea Bobu; Belinda Z. Li; Theodore R. Sumers; Ilia Sucholutsky; Nishanth Kumar; Thomas L. Griffiths 001; Julie A. Shah (HRI, 2024)

Learning with Language-Guided State Abstractions. - Andi Peng; Ilia Sucholutsky; Belinda Z. Li; Theodore R. Sumers; Thomas L. Griffiths 001; Jacob Andreas; Julie Shah (ICLR, 2024)

Learning Human-like Representations to Enable Learning Human Values. - Andrea Wynn; Ilia Sucholutsky; Tom Griffiths 001 (NeurIPS, 2024)

Concept Alignment. - Sunayana Rane; Polyphony J. Bruna; Ilia Sucholutsky; Christopher T. Kello; Thomas L. Griffiths 001 (CoRR, 2024)

Measuring Implicit Bias in Explicitly Unbiased Large Language Models. - Xuechunzi Bai; Angelina Wang; Ilia Sucholutsky; Thomas L. Griffiths 001 (CoRR, 2024)

A Rational Analysis of the Speech-to-Song Illusion. - Raja Marjieh; Pol van Rijn; Ilia Sucholutsky; Harin Lee; Thomas L. Griffiths 001; Nori Jacoby (CoRR, 2024)

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; et al. (CoRR, 2024)

Analyzing the Roles of Language and Vision in Learning from Limited Data. - Allison Chen; Ilia Sucholutsky; Olga Russakovsky; Thomas L. Griffiths 001 (CoRR, 2024)

Representational Alignment Supports Effective Machine Teaching. - Ilia Sucholutsky; Katherine M. Collins; Maya Malaviya; Nori Jacoby; Weiyang Liu; Theodore R. Sumers; Michalis Korakakis; Umang Bhatt; Mark K. Ho; Joshua B. Tenenbaum; Bradley C. Love; Zachary A. Pardos; et al. (CoRR, 2024)

Quantifying Spuriousness of Biased Datasets Using Partial Information Decomposition. - Barproda Halder; Faisal Hamman; Pasan Dissanayake; Qiuyi Zhang 001; Ilia Sucholutsky; Sanghamitra Dutta (CoRR, 2024)

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 (CoRR, 2024)

Building Machines that Learn and Think with People. - Katherine M. Collins; Ilia Sucholutsky; Umang Bhatt; Kartik Chandra; Lionel Wong; Mina Lee 002; Cedegao E. Zhang; Tan Zhi-Xuan; Mark K. Ho; Vikash Mansinghka 001; Adrian Weller; Joshua B. Tenenbaum; et al. (CoRR, 2024)

Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience. - Zhonghao He; Jascha Achterberg; Katie Collins; Kevin K. Nejad; Danyal Akarca; Yinzhu Yang; Wes Gurnee; Ilia Sucholutsky; Yuhan Tang; Rebeca Ianov; George Ogden; Chole Li; et al. (CoRR, 2024)

Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse. - Ryan Liu 001; Jiayi Geng; Addison J. Wu; Ilia Sucholutsky; Tania Lombrozo; Thomas L. Griffiths 001 (CoRR, 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 Comput. Sci., 2024)

Quantifying Knowledge Distillation using Partial Information Decomposition. - Pasan Dissanayake; Faisal Hamman; Barproda Halder; Ilia Sucholutsky; Qiuyi Zhang 001; Sanghamitra Dutta (AISTATS, 2025)

Large Language Models Assume People are More Rational than We Really are. - Ryan Liu 001; Jiayi Geng; Joshua C. Peterson; Ilia Sucholutsky; Thomas L. Griffiths 001 (ICLR, 2025)

Revisiting Rogers' Paradox in the Context of Human-AI Interaction. - Katherine M. Collins; Umang Bhatt; Ilia Sucholutsky (CoRR, 2025)

What is a Number, That a Large Language Model May Know It? - Raja Marjieh; Veniamin Veselovsky; Thomas L. Griffiths 001; Ilia Sucholutsky (CoRR, 2025)

On Benchmarking Human-Like Intelligence in Machines. - Lance Ying; Katherine M. Collins; Lionel Wong; Ilia Sucholutsky; Ryan Liu 001; Adrian Weller; Tianmin Shu; Thomas L. Griffiths 001; Joshua B. Tenenbaum (CoRR, 2025)

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 001; Raja Marjieh; R. Thomas McCoy; Andrew Nam; Ilia Sucholutsky; Veniamin Veselovsky; Liyi Zhang; Jian-Qiao Zhu; et al. (CoRR, 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 (CoRR, 2025)

Identifying, Evaluating, and Mitigating Risks of AI Thought Partnerships. - Kerem Oktar; Katherine M. Collins; José Hernández-Orallo; Diane Coyle; Stephen Cave; Adrian Weller; Ilia Sucholutsky (CoRR, 2025)

Using LLMs to Advance the Cognitive Science of Collectives. - Ilia Sucholutsky; Katherine M. Collins; Nori Jacoby; Bill D. Thompson; Robert D. Hawkins (CoRR, 2025)