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cs.CL2026
Probe with Participation Trophies: Random-Reward RL as a Probe of LLM Capability
Yu Mao, Lei Yu, Zining Zhu +6
We connect the spurious-reward paradox to a model's reachability and propose random-reward reinforcement learning (RL) as a useful tool for the probing enterprise, addressing a dec…
cs.CL2025
Can AI Validate Science? Benchmarking LLMs for Accurate Scientific Claim Evidence Reasoning
Shashidhar Reddy Javaji, Yupeng Cao, Haohang Li +3
Large language models (LLMs) are increasingly being used for complex research tasks such as literature review, idea generation, and scientific paper analysis, yet their ability to…
cs.CL2025
Truth Neurons
Haohang Li, Yupeng Cao, Yangyang Yu +2
Despite their remarkable success and deployment across diverse workflows, language models sometimes produce untruthful responses. Our limited understanding of how truthfulness is m…