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cs.LG2026
VFUSE: Virulent Feature Understanding with Sparse autoEncoders
Michael Yu, Matthew L. Olson
Generative models have shown remarkable progress in a variety of domains such as protein design, but such power enables the opaque generation of hazardous proteins. In this work, w…
cs.LG2026★ 18 cited
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1144
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
cs.LG2026
Data-Centric Interpretability for LLM-based Multi-Agent Reinforcement Learning
John Yan, Michael Yu, Yuqi Sun +3
Large language models (LLMs) are increasingly trained in complex Reinforcement Learning, multi-agent environments, making it difficult to understand how behavior changes over train…