Author

Jinyang Wu

h-index 3 View on Semantic Scholar

We have 4 of 12 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Jul 2026

From Proprietary to Open-Source: Bridging the Distribution Gap via Multi-Agent Protocol Distillation in Agentic Search

Multi-Agent Protocol Distillation (MAPD), a joint distillation and RL framework uses a structured, style-normalized protocol as an intermediate representation that generalizes robustly across diverse proprietary teachers while effectively mitigating the student policy from style drift and verbosity degeneration.

Junlin Liu, Jiangwang Chen, Zixin Song et al. · arXiv.org · 6 citations

Preprint Aug 2026

PCSD: Persistent Consistency for Self-Distillation in Agentic Reinforcement Learning

Persistent Consistency Self-Distillation (PCSD) is proposed, which derives token-level distillation weights from the local persistence of teacher-favoring signals, and combines adaptive windows with exponentially decayed aggregation to capture persistent relative teacher support.

Chunji Lv, Yangguang Wei, Junlin Liu et al. · 0 citations

Jul 2026

SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning

SEED (SElf-Evolving On-Policy Distillation), a self-evolving framework that converts completed on-policy trajectories into training-time hindsight skills and distills their behavioral effect back into the policy model, is proposed.

Jinyang Wu, Shuo Yang, Zhengxi Lu et al. · arXiv.org · 7 citations

Preprint Aug 2026

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning

This work proposes AgentOPSD, a critic-free, recursive method for turn-level credit assignment in agentic reinforcement learning that aggregates token-level teacher-student log-probability gaps into turn-level evidence and recursively updates a Bayesian belief state in log-odds space.

Zi-Han Wang, Zhengxi Lu, Zhiyuan Yao et al. · 1 citation