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AlgoEvo: Self-Evolving Agentic Search for Automated Algorithm Discovery

Paper recorded by Signals 4 on 2026-09-14 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-14 on arXiv · recorded by Signals 4 on 2026-09-15

Category: cs.AI · 人工智能 · first seen 2026-09-15

Abstract

Large language models have advanced automated algorithm discovery by synthesizing executable code, but existing frameworks trap them in rigid search pipelines with pre-defined control flows. This limitation restricts adaptive reasoning, blocks cross-paradigm transfer, and discards valuable execution feedback. We propose AlgoEvo, a unified agentic framework that transforms automated algorithm disco

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#77 most recent of 300 cs.AI papers we have recorded · ↑ newer: CiteGuard-RAG: A Validation-Centered AI System for Evidence-Grounded Q · ↓ older: Atria Dawn: The Dawn of Agentic Superintelligence
Cite this page: AlgoEvo: Self-Evolving Agentic Search for Automated Algorithm Discovery: the #77 most recent of 300 cs.AI papers we have recorded (as of 2026-09-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/algoevo-self-evolving-agentic-search-for-automated-algorithm-discovery.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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