arXiv 2610.27227 · cs.CL · 2026-10-19
Which Agent's Skill Should Change? Group-Relative Credit Assignment for Evolving Multi-Agent Teams
Yanan Ma, Yang Wang, David Le, Chenhan Yuan, Yizheng Sun, Guangwei Zhang, Chenghao Xiao, Chenghua Lin and 1 more
Mayo Clinic
In latest · #358 Added on 2026-10-25
One-line takeaway
Mayo Clinic's GRSE borrows from GRPO, rerunning each question under the same skill libraries and contrasting runs to credit specific agent-skill pairs, beating MASkills with up to +6.7 F1 on multi-hop HotpotQA.
梅奥诊所的 GRSE 借鉴 GRPO,在相同技能库下多次执行同一题并对比结果,把团队奖励归到具体 agent 和技能上,改进多 agent 的技能进化,在 HotpotQA 多跳题上提升 6.7 F1。
Read on arXiv PDF Hugging Face discussion Code
Topics & disciplines
More on Agents
- Raven: The Harness of Harnesses for Composable Agentic Intelligence ▲748
- False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents ▲642
- Omni-IO Skills: Harnessing Your Agent Omni-Native ▲485
- BizAgentBench: Unveiling Hidden Challenges in Deploying Long-Horizon Agents for Real-World Business ▲388
- Player-1: Learning to Play from Synthetic Experience ▲347
More on Reinforcement learning
- The Teacher Is a Direction, Not a Destination: Extrapolating RL-Induced Representation Residuals in On-Policy Distillation 2026-09-29 · ▲511
- Scaling Properties of Same-Family On-Policy Distillation 2026-09-26 · ▲327
- DiffusionART: Efficient, Stable and Scalable Reinforcement of Diffusion Models 2026-10-08 · ▲325
- Waypoint-OPD: Transferring RL-Induced Policy Shifts via Gated On-Policy Distillation 2026-10-15 · ▲214
- Agent-Reflex: Teaching Language Agents to Act Reflectively 2026-10-13 · ▲214
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-26.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.