Name: Agentic AI Use Case: Proactive Information Seeking for Non-Factoid Q&As
Start: 2025-11-21T14:00:00-06:00
End: 2025-11-21T15:00:00-06:00

[Multi-Agent Proactive Information Seeking with Adaptive LLM Orchestration for Non-Factoid Question Answering](https://dl.acm.org/doi/pdf/10.1145/3711896.3737249)

The proliferation of complex non-factoid questions in modern information seeking (IS) systems exposes critical limitations in conventional Retrieval-Augmented Generation (RAG) approaches, particularly their static search strategies and the lack of systematic multi-source information integration capabilities. Facing these limitations, we present PASS (Proactive Agent-driven Search System), a novel multi-agent framework that operationalizes human-like proactive search strategies through five specialized agents: Revealer for intent analysis, Navigator for search planning, Seeker/Reader for adaptive retrieval, and Writer for response synthesis, systematically expanding the search space through iterative query refinement and multi-perspective knowledge integration. Crucially, our framework demonstrates remarkable adaptability to mid-sized LLMs, demonstrating its scalability in resource-constrained environments.

Slides for past meetups posted: [Github](https://github.com/YanXuHappygela/LLM-reading-group/)
Recordings have been posted at: [YanAITalk](https://www.youtube.com/@yanaitalk/videos)

Feel free to reach out if you want to present a paper or a use case at upcoming meetups!

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Yan Xu

Houston Machine Learning

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Artificial Intelligence

Big Data

Machine Learning

Deep Learning

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Predictive Analytics

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Agentic AI Use Case: Proactive Information Seeking for Non-Factoid Q&As

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