Extending AI for Research to the Humanities: A Multi-Agent Framework for Evidence-Grounded Scholarship 文章
ArXiv CS.CL2026-06-01NEWSen作者: Yating Pan (Department of Information Management, Peking University, Research Center for Digital Humanities, Peking University), Jiajun Zhang (Research Center for Digital Humanities, Peking University), Jun Wang (Department of Information Management, Peking University, Institute for Artificial Intelligence, Peking University), Qi Su (School of Foreign Languages, Peking University, Institute for Artificial Intelligence, Peking University)
摘要
arXiv:2605.30947v1 Announce Type: new Abstract: LLM-based research agents have advanced rapidly in science and engineering, where research is organized around executable experiments, code, and quantitative signals. Humanities scholarship, however, requires a different mode of reasoning: interpretive, evidence-grounded argument over primary sources, where scholarly value depends on faithful quotation, verifiable provenance, and close reading. Existing research agents remain largely optimized for execution and retrieval, not evidence-grounded interpretive reasoning. To address this gap, we introduce SPIRE (Scholarly-Primitives-Inspired Research Engine), a multi-agent framework for evidence-grounded humanities scholarship.