Author

Yu-Gu Li

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#artificial intelligence Preprint Sep 2026

Can We Trust the Teacher? Decoupled Credit Direction-Magnitude for Self-Distillation

Decoupled Credit Self-Distillation is introduced, which theoretically decouples credit direction and magnitude into two reliable signals and uses them to calibrate privileged teacher supervision, enabling step-to-token credit assignment for policy optimization.

Yu-Gu Li, Ze-Hong Cao, Pei-Zhen Li et al. · 0 citations

#artificial intelligence Preprint Aug 2026

RTPO: Reverse-Turn Policy Optimization for Stabilizing Agentic RL Training

This work proposes Reverse-Turn Policy Optimization (RTPO), which organizes multi-turn rollouts as sparse reverse trees and performs turn-level policy updates in temporal reverse order, aligning each decision with its downstream continuation.

Yu-Gu Li, Ze-Hong Cao, Jiang-Lin Qiao et al. · 1 citation