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SelfSearch: Reward-Free Search for Self-Improving Agents

Paper recorded by Signals 4 on 2026-09-29 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-29 on arXiv · recorded by Signals 4 on 2026-09-30

Category: cs.CL · 自然语言处理 · first seen 2026-09-30

Abstract

Advances in the coding capabilities of LLM agents allow them to inspect and modify their own instructions, tools, and execution procedures. Existing approaches use this ability to search for improved agents through repeated downstream evaluation, which incurs substantial costs and ties the search to the evaluated tasks. We introduce \textbf{SelfSearch}, a reward-free search procedure in which agen

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#13 most recent of 292 cs.CL papers we have recorded · ↑ newer: On Trajectory-Aware Training for Masked Diffusion Language Models · ↓ older: Retrieving Biblical Intertextual References in Karen Blixen's Seven Go
Cite this page: SelfSearch: Reward-Free Search for Self-Improving Agents: the #13 most recent of 292 cs.CL papers we have recorded (as of 2026-09-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/selfsearch-reward-free-search-for-self-improving-agents.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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