AI RESEARCH
SciNet: Evaluating AI Agents in Relation-Aware Scientific Literature Retrieval
arXiv CS.CL
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ArXi:2601.03260v2 Announce Type: replace-cross AI agents have seen widespread adoption in information retrieval for scientific research, giving rise to tools such as Deep Research. However, existing retrieval agents mainly rely on keyword- or embedding-based methods. While effective at capturing content-level similarities, they struggle to understand complex relational networks among scientific papers, such as identifying corroborating or conflicting studies and tracing technological lineages.