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…

Ankur Samanta, Yonathan Efroni, Paul Sajda, Kaveh Hassani, Anirudh Goyal·arXiv — cs.AI

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Key Takeaways

01.Long-horizon research agents must decide both how to investigate and what to investigate next as evidence accumulates
02.This is hard to learn because such decisions are sparse in long execution traces, and their consequences may emerge several investigations later
03.We introduce…

This material is provided as an extended analytical summary.

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