新闻
GEPA-Curator: Curated Learning for Self Improving Agents
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- GEPA-Curator filters which agent failures teach prompt optimizers, using task curation and successful trajectory retrieval to improve learning signals.
- 为何重要
- Engineers building multi-turn LLM agents need this when prompt optimization learns from noisy or unreliable failures across complex environments.
- 注意
- Tested on specific benchmarks with Gemini and Claude; unclear how curation strategy generalizes to other agent types or domains.
- agent
- agentic
- llm
- language model
- prompt
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