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!

**Note:** You must have a Zoom account to login (free account is sufficient). Link and password will be shared three days before the meeting.

Yan Xu

Houston Machine Learning

Technology

Artificial Intelligence

Big Data

Machine Learning

Deep Learning

Data Visualization

Predictive Analytics

Data Science

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

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Houston Machine Learning

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

Houston Machine Learning

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