Eric Bigelow

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Member of Technical Staff at Goodfire AI, PhD in Cognitive Psychology from Harvard. Previously at NTT Research, Uber, U.Rochester

My primary research focus is interpretability and evaluation of large language models, in particular in-context learning, reasoning, uncertainty, and cognition more generally.

I am also broadly interested in work at the intersection of AI and cognitive science, as well as computational cognitive modeling, mental imagery, and program comprehension.

selected publications

  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. Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
    Eric Bigelow*, Daniel Wurgaft*, YingQiao Wang, Noah Goodman, Tomer Ullman, Hidenori Tanaka, and Ekdeep Singh Lubana
    arXiv preprint arXiv:2511.00617, 2025
    arXiv
  3. Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space
    Eric Bigelow, Raphaël Sarfati, Daniel Wurgaft, Owen Lewis, Thomas McGrath, Jack Merullo, Atticus Geiger, and Ekdeep Singh Lubana
    arXiv preprint arXiv:2605.12412, 2026
    arXiv
  4. Towards a Cognitive Science of Large Language Models
    Eric Bigelow
    Harvard University, 2026
    HTML
  5. 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