Personalized Auto-Research: Towards a True AI Co-Scientist

• 类型：arxiv
• 标识：2608.14881
• 链接：https://arxiv.org/abs/2608.14881
• 主分类：rag
• 形态：method
• 被引：0
• 被引来源：Semantic Scholar
• S2被引：0
• 影响力被引：0
• TLDR：This work introduces the problem of personalized auto-research, which conditions every stage of the research process on a representation of the individual researcher, and proposes a general and flexible framework that threads a graph-grounded researcher context through retrieval, hypothesis search, experimentation, writing, and review.
• 待LLM分类：否
• 标题中文：Personalized Auto-Research：迈向真正的 AI 共同科学家
• TLDR中文：本文提出 personalized auto-research 问题，将研究流程的每个阶段都以个体研究者的表征为条件，并提出了一个通用且灵活的框架，将基于图的研究者上下文贯穿于检索、假设搜索、实验、写作与评审之中。
• 来源文件：
• /inbox/tom/_candidates/2026-08-19-agent-rag-longcontext-candidates.json
• [S2 enrich]