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Hui Shao

2 accepted papers

2026

OVLR: Efficient, Scalable, and Robust Training via Output-Level Variance-Reduced Likelihood Ratio

ICML 2026poster

Gradient-based optimization is fundamental to deep learning, yet standard backpropagation (BP) is inherently limited by the requirement of differentiability, rendering it brittle when encountering piecewise-constant objectives with vanishing gradients (e.g., hard 0-1 loss) or black-box feedback. Whi…

Cited by 0SourceScholar
2026

RiskPO: Risk-based Policy Optimization with Verifiable Reward for LLM Post-Training

ICLR 2026poster

Reinforcement learning with verifiable reward has recently emerged as a central paradigm for post-training large language models (LLMs); however, prevailing mean-based methods, such as Group Relative Policy Optimization (GRPO), suffer from entropy collapse and limited reasoning gains. We argue that…

Cited by 0SourcecodeScholar