OptGraph: Large Language Models Enhanced Evolutionary Optimization Via Graph Retrieval-Augmented Generation
- 类型:arxiv
- 标识:2607.27918
- 链接:http://arxiv.org/abs/2607.27918v1
- 主分类:rag
- 形态:method
- 被引:1
- 被引来源:Semantic Scholar
- S2被引:1
- OpenAlex被引:0
- 影响力被引:0
- TLDR:OptGraph is the first optimization agentic workflow that introduces graph retrieval-augmented generation (GraphRAG) and first constructs reusable experience as a typed graph, capturing the relationships among modeling patterns, problem formalization, implementation details, and error corrections.
- OpenAlex ID:W7171955510
- OpenAlex DOI:10.48550/arxiv.2607.27918
- DOI:10.48550/arxiv.2607.27918
- DOI来源:OpenAlex
- 开放获取:green
- 开放获取链接:https://doi.org/10.48550/arxiv.2607.27918
- OpenAlex更新:2026-08-26
- 待LLM分类:否
- 标题中文:OptGraph:通过图 RAG 增强的大语言模型进化优化
- TLDR中文:OptGraph 是首个引入 GraphRAG 的优化 agentic workflow,首次将可复用经验构建为类型化 graph,刻画建模模式、问题形式化、实现细节与错误修正之间的关系。
- 来源文件:
- /inbox/tom/_candidates/2026-07-31-agent-rag-longcontext-candidates.json
- [S2 enrich]
- [OpenAlex backfill]