Author

Chenyi Zhuang

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Preprint Aug 2026

Teach the Magnitude, Not the Direction: Verifier-Bounded Credit Assignment for Multi-Turn Multi-step LLM Agents

A hierarchical credit assignment framework that retains RL's verifier-bounded ceiling while incorporating dense token-level signals from a privileged self-teacher is introduced, unlocking dense credit assignment without sacrificing the verifier-bounded ceiling.

Zechuan Wang, Siyuan Lu, Hongxuan Zhang et al. · 1 citation

#machine learning Preprint Aug 2026

Last Step Matters: Early Uncertainty Cannot Predict Failure in Long-Horizon Agents

An underlying mechanism explaining the gap in uncertainty quantification is identified: path switching, where agents frequently abandon their current search direction in-trajectory, breaking the link between early signal and final outcome.

Zongrun Li, Cheng-Yue Yu, Lei Zang et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Rubric-to-Code Credit Assignment for Reinforcement Learning

A reinforcement learning framework that converts rubric-level functional feedback into localized optimization signals over generated code and aligns evaluator-generated textual attributions with responsible code spans and generated tokens is proposed.

Rui Jin, Jikai Chen, Yihang Chen et al. · 0 citations