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EvoDuet: Bilevel Co-Evolution of Web Searching and Task Solving for Scientific Discovery

Paper recorded by Signals 4 on 2026-09-30 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-30 on arXiv · recorded by Signals 4 on 2026-10-01

Category: cs.CL · 自然语言处理 · first seen 2026-10-01

Abstract

Evolutionary search with large language models (LLMs) can stall when progress requires external knowledge the model lacks. Supplying relevant documents helps, but simply adding web search tool can keep returning the same pages as solutions change. We introduce EvoDuet, a bi-level optimization method that co-evolves solutions and search queries with fixed model parameters. At each iteration, a retr

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#1 most recent of 299 cs.CL papers we have recorded · ↓ older: Decision-Oriented Recommendation Reranking: An Empirical Study of Jev
Cite this page: EvoDuet: Bilevel Co-Evolution of Web Searching and Task Solving for Scientific Discovery: the #1 most recent of 299 cs.CL papers we have recorded (as of 2026-09-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/evoduet-bilevel-co-evolution-of-web-searching-and-task-solving-for-scientific-di.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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