arXiv 2610.00906 · cs.AI · 2026-10-01
ActiveSaddler: Automated Curriculum Learning for Agent Harness Optimization
Sungho Park, Wonjoong Kim, Jue Zhang, Wook-Shin Han, Pengfei Gao, Chanyoung Park, Yongqiang Yao, Rao Fu 等 11 人
Microsoft
在最新榜 #246 本站收录于 2026-10-21
一句话要点
微软 ActiveSaddler 让训练场景随智能体外壳一起自适应调整，实现自动课程式的外壳优化。
Microsoft's ActiveSaddler adapts the training curriculum alongside the evolving agent harness for automated harness optimisation.
阅读 arXiv 原文 PDF Hugging Face 讨论 项目页
主题与学科
同主题：智能体
- Raven: The Harness of Harnesses for Composable Agentic Intelligence ▲748
- False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents ▲642
- BizAgentBench: Unveiling Hidden Challenges in Deploying Long-Horizon Agents for Real-World Business ▲490
- Omni-IO Skills: Harnessing Your Agent Omni-Native ▲485
- Player-1: Learning to Play from Synthetic Experience ▲348
数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-22。
要点由本站根据摘要自写，不转载摘要原文，请阅读原文。