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AI Research
arXiv CS.AI·Jun 9·5 min read
Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)
TL;DR
Academic search systems have traditionally focused on document retrieval, lacking integration with advanced technologies. The CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS) explored how generative AI can enhance these systems by supporting summarization, recommendation, and conversational interaction.
✦ Why It Matters
Engineers can leverage insights from the workshop to design more effective academic search systems using generative AI techniques.
Key Takeaways
- Explore GenAI applications in academic search for better user engagement.
- Focus on transparency and credibility in search system design.
- Utilize summarization and recommendation features to enhance research.
- Foster community partnerships to advance GenAI research initiatives.
Full Summary
The workshop gathered experts in human information interaction and information retrieval to address the impact of generative AI (GenAI) on academic search systems. Participants identified three main themes: foundational principles, practical applications, and the concept of search-as-learning.
Discussions emphasized the need for academic search systems to promote transparency, credibility, and research integrity while supporting cognitive processes. The workshop highlighted various guiding theories and design principles for developing human-centered GenAI-enhanced search systems.
Participants also explored partnerships and community-building efforts to advance research in this area. Overall, the event showcased a strong interest in the intersection of GenAI and academic search, with numerous ongoing and emerging research initiatives.