publications

publications in reverse chronological order.

* = equal first author

2025

  1. Forking paths in neural text generation
    Eric Bigelow, Ari Holtzman, Hidenori Tanaka, and Tomer Ullman
    International Conference on Learning Representations (ICLR), 2025
    arXiv
  2. Language models assign responsibility based on actual rather than counterfactual contributions
    Yang Xiang*, Eric Bigelow*, Tobias Gerstenberg, Tomer Ullman, and Samuel J Gershman
    In Proceedings of the Annual Meeting of the Cognitive Science Society, 2025
    PDF
  3. Evaluating Self-Orienting in Language and Reasoning Models
    Eric Bigelow*, Zergham Ahmed*, and Tomer Ullman
    ICML Workshop on Assessing World Models: Methods and Metrics for Evaluating Understanding, 2025
  4. Let’s Simulate Frame-by-Frame: In-Context Physical Simulations with Vision-Language Models
    Yingqiao Wang*, Eric Bigelow*, and Tomer Ullman
    ICML Workshop on Assessing World Models: Methods and Metrics for Evaluating Understanding, 2025
  5. Are language models aware of the road not taken? Token-level uncertainty and hidden state dynamics
    Amir Zur*, Eric Bigelow*, Atticus Geiger, and Ekdeep Singh Lubana
    ICML Workshop on Actionable Interpretability, 2025
  6. People evaluate the algorithms that drive agents’ behavior
    Eric Bigelow, and Tomer Ullman
    Open Mind (under revision), 2025
  7. On (Not) Seeing Your Self: Some People May Lack Third-Person Imagery
    Eric Bigelow, and Tomer Ullman
    In Society for Philosophy and Psychology, 2025

2024

  1. In-Context Learning Dynamics with Random Binary Sequences
    Eric Bigelow, Ekdeep Singh Lubana, Robert P Dick, Hidenori Tanaka, and Tomer Ullman
    International Conference on Learning Representations (ICLR), 2024
    arXiv
  2. Foundational challenges in assuring alignment and safety of large language models
    Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, and  others
    Transactions in Machine Learning Research (TMLR), 2024
    HTML

2023

  1. Mechanistic mode connectivity
    Ekdeep Singh Lubana, Eric Bigelow, Robert P Dick, David Krueger, and Hidenori Tanaka
    International Conference on Machine Learning (ICML), 2023
  2. Subjective Randomness and In-Context Learning
    Eric Bigelow, Ekdeep Singh Lubana, Robert P Dick, Hidenori Tanaka, and Tomer Ullman
    In NeurIPS Workshop on UniReps: Unifying Representations in Neural Models, 2023
  3. Non-commitment in mental imagery
    Eric Bigelow, John P McCoy, and Tomer Ullman
    Cognition, 2023

2022

  1. People’s evaluation of programs that drive agents’ behavior
    Eric Bigelow, and Tomer Ullman
    In Proceedings of the Annual Meeting of the Cognitive Science Society, 2022
  2. Mechanistic Lens on Mode Connectivity
    Ekdeep Singh Lubana, Eric Bigelow, Robert Dick, David Krueger, and Hidenori Tanaka
    NeurIPS Workshop on Distribution Shifts: Connecting Methods and Applications, 2022
  3. Opening the black box: People evaluate agents based on the algorithms that drive their behavior.
    Eric Bigelow, and Tomer Ullman
    In Society for Philosophy and Psychology, 2022

2016

  1. Inferring priors in compositional cognitive models.
    Eric Bigelow, and Steven T Piantadosi
    Proceedings of the Annual Meeting of the Cognitive Science Society, 2016
  2. A large dataset of generalization patterns in the number game
    Eric Bigelow, and Steven Piantadosi
    Journal of Open Psychology Data, 2016
  3. Tales of two cities: Using social media to understand idiosyncratic lifestyles in distinctive metropolitan areas
    Tianran Hu, Eric Bigelow, Jiebo Luo, and Henry Kautz
    IEEE Transactions on Big Data, 2016

2015

  1. On the need for imagistic modeling in story understanding
    Eric Bigelow, Daniel Scarafoni, Lenhart Schubert, and Alex Wilson
    Biologically Inspired Cognitive Architectures, 2015