Samuel Schapiro

I am an interdisciplinary scholar studying the science of intelligence. My work bridges cognitive science, computer science, and the philosophy of science to advance the following research directions:

Developing novel AI methods and systems that exhibit creative behavior.
Uncovering the fundamental, scientific principles of creativity governing minds and machines.

Previously, I was a visiting researcher at the Simons Institute for the Theory of Computing, Berkeley. I did my undergrad at the University of Illinois, Urbana-Champaign, where I studied theoretical computer science.

Email / Google Scholar / GitHub / LinkedIn / Bookshelf

News

[Jul 2026] Coming soon!
[Jun 2026] New preprint TwistBench: Benchmarking Transformational Creativity in LLMs via Literary Plot Twists up!
[May 2026] 2/2 papers accepted at the ICML 2026 Workshop on Generative AI & Creativity.
[Apr 2026] Received the Lambda AI Research Grant.
[Jun 2025] 🏆 Best Short Paper Award at ICCC 2025 for Transformational Creativity in Science: A Graphical Theory.
[May 2025] 2/2 papers accepted at ICCC 2025.
[May 2024] Pivoted from ML theory to cognitive science.

A post by @samschapiro on X

Research Areas

I. Measuring the Creativity of AI

Benchmarks and tests of creativity, especially more complex forms such as transformational and scientific creativity.

TwistBench: Benchmarking Transformational Creativity in LLMs via Literary Plot Twists S. Schapiro, A. Gladstone, H. Ji, R. E. Beaty Under review, COLM 2026 Workshop on Scientific Understanding of Foundation Models.
Assessing the Creativity of Large Language Models: Testing, Limits, and New Frontiers S. Schapiro, A. Gladstone, J. Black, H. Ji Preprint
Do Semantic Distance Tests Actually Predict Creativity in Large Language Models? S. Schapiro, A. Gladstone, J. Black, H. Ji Accepted at the ICML 2026 Workshop on Generative AI & Creativity. Under review, NeurIPS.

II. Improving the Creativity of AI

Methods and systems that make models more creative.

CreativityNeuro: Steering Language Model Weights to Improve Divergent Thinking and Reduce Mode Collapse S. Schapiro, C. Francisco Park, F. Sosa, L. R. Varshney Third Conference on Language Modeling (COLM). Accepted at the ICML 2026 Workshop on Generative AI & Creativity.
Spark: A System for Scientifically Creative Idea Generation A. Sanyal, S. Schapiro, S. Shashidhar, R. Moon, L. R. Varshney, D. Hakkani-Tur Proceedings of the 16th International Conference on Computational Creativity (ICCC)

III. Theories and Foundations of Creativity

Formal accounts of what creativity is and how it manifests in minds and machines.

Artificial Creative Intelligence S. Schapiro, R. E. Beaty Invited Chapter, Cambridge Handbook of Creativity (3rd ed.), Cambridge University Press. Eds. J. C. Kaufman & R. J. Sternberg. In preparation.
Combinatorial Creativity: A New Frontier in Generalization Abilities S. Schapiro, S. Shashidhar, A. Gladstone, J. Black, R. Moon, D. Hakkani-Tur, L. R. Varshney Preprint
Transformational Creativity in Science: A Graphical Theory S. Schapiro, J. Black, L. R. Varshney Proceedings of the 16th ICCC — Best Short Paper Award

Service

Conference Reviewer: ICML 2026, COLM 2026, NeurIPS 2026
Workshop Reviewer: NeurIPS 2024 Creativity & Generative AI, ICML 2026 Creativity & Generative AI