arXiv (All)
open access
Evolution or Illusion? Rethinking Evaluation in LLM Evolutionary Search
LLM-driven evolutionary search finds programs by launching seeds and iterating each one. Papers report a single budget setting, usually one seed run for a fixed number of iterations, and rank methods from that one point. We show this is not enough. We evaluate three evolutionary search strategies on
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Evolutionary Ensemble Search: Council-Guided Program Evolution with Persistent Memory#1011322
- Towards Certificate-Driven Software Porting: A Self-Improving Agentic Harness for Scientific Program Optimization#1119142
- Towards Certificate-Driven Software Porting: A Self-Improving Agentic Harness for Scientific Program Optimization#1108844
- Batched Feedback and the Random-Access Wall in Search-Based Graph Construction#1108876
- Batched Feedback and the Random-Access Wall in Search-Based Graph Construction#1104692
Record · ID 1014383
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive