Summary of Into the Unknown Unknowns: Engaged Human Learning Through Participation in Language Model Agent Conversations, by Yucheng Jiang et al.
Into the Unknown Unknowns: Engaged Human Learning through Participation in Language Model Agent Conversations
by Yucheng Jiang, Yijia Shao, Dekun Ma, Sina J. Semnani, Monica S. Lam
First submitted to arxiv on: 27 Aug 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Information Retrieval (cs.IR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed Collaborative STORM (Co-STORM) system allows users to discover unknown unknowns by observing and occasionally steering conversations among multiple language model agents. Unlike traditional question-answering systems, Co-STORM enables serendipitous learning through user interaction. The system tracks the discourse using a dynamic mind map and generates a comprehensive report as takeaways. To evaluate its performance, the WildSeek dataset was constructed and Co-STORM outperformed baseline methods on both discourse trace and report quality. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Co-STORM is a new way to help people learn by having conversations with multiple AI agents. Instead of asking questions one by one, users can listen in on a conversation between the agents and occasionally join in. The system helps users keep track of what’s being discussed and generates a summary at the end. This approach makes it easier for people to discover new information that they might not have thought to ask about. |
Keywords
» Artificial intelligence » Discourse » Language model » Question answering
