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cs.LG2025
Auto-Rubric: Learning From Implicit Weights to Explicit Rubrics for Reward Modeling
Lipeng Xie, Sen Huang, Zhuo Zhang +9
Conventional reward modeling relies on gradient descent over neural weights, creating opaque, data-hungry "black boxes." We propose a paradigm shift from implicit to explicit rewar…
cs.AI2025
Voting with the Graph: Stable RLAIF via Topological Consistency Maximization
Boyin Liu, Zhuo Zhang, Sen Huang +8
Reinforcement Learning from AI Feedback (RLAIF) relies on LLM judges as preference measurement instruments, yet these instruments are fundamentally limited by random measurement er…