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标题为英语Learning What to Investigate Next: Meta-Reasoning for Long-Horizon Research Agents
Long-horizon research agents must decide both how to investigate and what to investigate next as evidence accumulates. This is hard to learn because such decisions are sparse in long execution traces, and their consequences may emerge several investigations later. We introduce…
arXiv — cs.AI作者: Ankur Samanta, Yonathan Efroni, Paul Sajda, Kaveh Hassani, Anirudh Goyal2026年10月5日 (10月5日)
提供 1 种语言版本AI 摘要：要点
- Long-horizon research agents must decide both how to investigate and what to investigate next as evidence accumulates
- This is hard to learn because such decisions are sparse in long execution traces, and their consequences may emerge several investigations later
- We introduce…
Research
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Learning What to Investigate Next: Meta-Reasoning for Long-Horizon Research Agents
标签：#arXiv
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