Lindsay Smith

Papers

* indicates equal contribution.

8. DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking

Matt L. Wiemann*, Lindsay M. Smith*, Peter Melchior, Siddharth Mishra-Sharma, Andrew Gordon Wilson, Pavel Izmailov, Carolina Cuesta-Lázaro (2026)

Under review

Leaderboard/project page

7. Chain-of-Thought Injection as an Inference-Time Safety Intervention

LMS*, Ananya Malik*, Edward James Young, Puria Radmard, Cameron Tice, Hannes Whittingham (2026)

ICLR 2026 Workshop on Logical Reasoning of LLMs

6. Large language models and the entropy of English

Colin Scheibner*, LMS*, William Bialek (2025)

Under review

5. ALICE: An Interpretable Neural Architecture for Generalization in Substitution Ciphers

Jeff Shen* and LMS* (2025)

Preprint

Project page + demo

4. When can in-context learning generalize out of task distribution?

Chase Goddard, LMS, Vudtiwat Ngampruetikorn*, David J. Schwab* (2025)

ICML 2025

3. Model Recycling: Model component reuse to promote in-context learning

LMS, Chase Goddard, Vudtiwat Ngampruetikorn*, David J. Schwab* (2024)

NeurIPS 2024 SciForDL Workshop

2. Specialization-generalization transition in exemplar-based in-context learning

Chase Goddard, LMS, Vudtiwat Ngampruetikorn*, David J. Schwab* (2024)

NeurIPS 2024 SciForDL Workshop

1. Learning continuous chaotic attractors with a reservoir computer

LMS, Jason Z. Kim, Zhixin Lu, Dani S. Bassett (2022)

Chaos journal · Editor's Pick

Scilight press summary

Recent Presentations

American Physical Society (APS) Global Summit 2026

Talk: "Universality of LLM mechanisms across scale and diversity"

Conference abstract

Meta 2025 PhD Forum

Poster: “ALICE: An Interpretable Neural Architecture for Generalization in Substitution Ciphers”

View poster

APS Global Summit 2025

Topical Group on Statistical and Nonlinear Physics (GSNP) Student Speaker Award Finalist

Talk: "Multi-Agent Debate: Analyzing Consensus in Networks of LLM Agents"

Conference abstract

Background

Previously, I was an undergraduate at the University of Pennsylvania where I majored in physics (with honors), minored in mathematics and French and Francophone studies, and graduated cum laude. My undergrad research advisor was Dani Bassett, and I researched human white matter brain networks, the human perception of the stars in the night sky, and abstraction in reservoir computers (a type of RNN).

Before undergrad, I worked on a project at WSU designing a flux spectrometer for the Deep Underground Neutrino Experiment (DUNE) at Fermilab, advised by Holger Meyer.