Author

Zhao-Ran Wang

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#natural language process... Preprint Oct 2026

Probe with Participation Trophies: Random-Reward RL as a Probe of LLM Capability

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 decade-long debate over what probing performance actually reveals about a model. There are two prevailing explanations for the surprising findi...

Yu-Zhu Mao, Lei Yu, Zi-Ning Zhu et al. · 0 citations

#artificial intelligence Mar 2026

Farther the Shift, Sparser the Representation: Analyzing OOD Mechanisms in LLMs

This study provides new mechanistic insights into how LLMs internalize OOD challenges, and designs Sparsity-Guided Curriculum In-Context Learning (SG-ICL), a strategy that explicitly uses representation sparsity to schedule few-shot demonstrations, leading to considerable performance enhancements.

Ming-Yu Jin, Yu-Tong Yin, Jingcheng Niu et al. · arXiv.org · 3 citations