collaborators

5 papers

cs.AI2026

Automatic Layer Selection for Hallucination Detection

Xinpeng Wang, William X. Cao, Andrew Gordon Wilson +1

Recent studies on hallucination detection have shown that hallucination-related signals are more strongly encoded in intermediate layers than in the final layer of large language m…

cs.LG2026

Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay

Martin Marek, Dongkyu Cho, Shikai Qiu +3

Models trained on a new task typically degrade on prior tasks, a phenomenon known as forgetting. Traditionally, mitigating forgetting has required replaying stored exemplars from p…

stat.ML2026

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

Matt L. Wiemann, Lindsay M. Smith, Peter Melchior +4

Frontier LLMs now perform strongly across a wide range of physics evaluations, but it is hard to disentangle genuine reasoning from recall of established science. We introduce Disc…

cs.LG2026

From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence

Marc Finzi, Shikai Qiu, Yiding Jiang +3

Can we learn more from data than existed in the generating process itself? Can new and useful information be constructed from merely applying deterministic transformations to exist…

cs.LG2026

Reliable and Responsible Foundation Models: A Comprehensive Survey

Xinyu Yang, Junlin Han, Rishi Bommasani +49

Foundation models, including Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Image Generative Models (i.e, Text-to-Image Models and Image-Editing Models), a…