Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Cheng Yang

h-index 0 View on Semantic Scholar

3 papers indexed here

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.

Book Open access Aug 2026

Find Tailored Step Example for Next Step: a Targeted Step-wise Retrieval Framework for Guiding LLM Reasoning

This work proposes Step-wise Training for In-context Reasoning (STIR), a model to dynamically decide when to retrieve a single logically consistent next step, just using the current problem and its intermediate state as the query.

Cheng Yang, Zhenya Huang, Liyang He et al. · 0 citations
Preprint Aug 2026

Beyond Imitation: Filtering On-Policy Distillation by Reasoning Progress

This work proposes Reasoning-Progress-Aware Reward Filtering for On-Policy Distillation (R2-OPD), which constructs two within-trajectory rankings of reasoning spans, one from teacher-derived rewards and the other from independently estimated progress reward.

Chen Yang, Hai-Yuan Wan, Rengrong Xiong et al. · 2 citations
Book Open access Aug 2026

Find Tailored Step Example for Next Step: a Targeted Step-wise Retrieval Framework for Guiding LLM Reasoning

This work proposes Step-wise Training for In-context Reasoning (STIR), a model to dynamically decide when to retrieve a single logically consistent next step, just using the current problem and its intermediate state as the query.

Cheng Yang, Zhenya Huang, Liyang He et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.