arXiv:2606.08936cs.IRcs.AI2026-06

探讨生成式AI如何重塑学术搜索与研究范式

Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)

论文配图:Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)
图 1 · 摘自论文原文
  • 聚焦生成式AI在学术搜索中的应用,推动从文档检索到智能交互的转型
  • 强调透明性、可信度与学术诚信在系统设计中的核心地位
  • 适合关注AI辅助科研、人机信息交互的研究者与实践者

本报告总结了2026年CHIIR研讨会关于生成式AI与学术搜索(GAI&AS)的工作坊内容,探讨生成式AI如何重塑学术搜索系统与研究实践。工作坊汇聚人机信息交互与信息检索领域学者,围绕生成式AI融入学术搜索所面临的挑战与机遇展开讨论,推动学术搜索系统从传统文档检索向摘要生成、推荐、知识整合及对话交互演进。参与者聚焦三大主题:基础理论与原则、应用场景与机遇、搜索即学习。会议强调学术搜索系统在保障透明性、可信度、研究完整性及支持高阶认知过程方面的重要作用,并探讨了指导理论、设计原则、方法论、合作机制与社区建设等议题,展现了该交叉领域的广泛研究兴趣与多样化的前沿探索。

原文摘要 · Abstract (English)

This report summarizes the CHIIR 2026 Workshop on Generative AI and Academic Search (GAI\&AS), which examined how GenAI is reshaping academic search systems and research practices. The workshop brought together researchers in human information interaction and information retrieval to explore key challenges and opportunities in designing and evaluating future academic search systems that integrate GenAI, moving beyond traditional document retrieval to support summarization, recommendation, synthesis, and conversational interaction. Participants' interests and discussions focused on three thematic clusters: foundations and principles, applications and opportunities, and search-as-learning. Across these themes, the workshop highlighted the importance of academic search systems in supporting transparency, credibility, research integrity, and long-term scholarly needs, as well as in fostering higher-order cognitive processes. Participants discussed guiding theories, design principles, methodological approaches, partnerships, and community-building efforts aimed at advancing human-centered GenAI-enhanced academic search systems. Overall, the workshop demonstrated strong community interest and a diverse range of ongoing and emerging research initiatives at the intersection of GenAI and academic search.

生成式AI学术搜索人机交互

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。