Summary of Tell Me More! Towards Implicit User Intention Understanding Of Language Model Driven Agents, by Cheng Qian et al.
Tell Me More! Towards Implicit User Intention Understanding of Language Model Driven Agents
by Cheng Qian, Bingxiang He, Zhong Zhuang, Jia Deng, Yujia Qin, Xin Cong, Zhong Zhang, Jie Zhou, Yankai Lin, Zhiyuan Liu, Maosong Sun
First submitted to arxiv on: 14 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)
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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 This paper introduces Intention-in-Interaction (IN3), a benchmark designed to assess users’ implicit intentions through explicit queries. It proposes incorporating model experts into agent designs to enhance user-agent interaction. The researchers empirically train Mistral-Interact, a powerful model that proactively assesses task vagueness and refines it into actionable goals before executing downstream tasks. They evaluate the enhanced agent system within the XAgent framework, demonstrating improved efficiency in identifying vague tasks, recovering missing information, setting precise goals, and minimizing redundant tool usage. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about making computers better understand what humans mean when they give instructions. Sometimes these instructions are unclear or open-ended, which can cause problems for computer programs that rely on them. The researchers developed a new way to test how well a computer program understands human intentions by asking follow-up questions and refining its understanding of the task at hand. They also created a special model that can do this and tested it with real-world data. The results show that their approach is more effective than previous methods in understanding vague instructions, filling in missing information, setting clear goals, and avoiding unnecessary steps. |
