Summary of Synthetic Dialogue Dataset Generation Using Llm Agents, by Yelaman Abdullin et al.
Synthetic Dialogue Dataset Generation using LLM Agents
by Yelaman Abdullin, Diego Molla-Aliod, Bahadorreza Ofoghi, John Yearwood, Qingyang Li
First submitted to arxiv on: 30 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 presents an innovative approach to generating linear programming (LP) models by developing a goal-oriented conversational agent that engages with users to elicit required information. To achieve this, the authors propose prompt engineering techniques and design two agents that “talk” to each other, one acting as the conversational agent and the other simulating user input. The conversation is guided by text descriptions of linear problems from NL4Opt, aiming to retrieve key information about the original problem description. Additionally, the paper introduces an extrinsic evaluation framework to assess the quality of generated dialogues by comparing summaries with original problem descriptions. Human and automatic evaluations, including a GPT-4-based approach, demonstrate good overall dialogue quality, though further research is needed to refine the GPT-4 evaluation metrics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The goal of this paper is to create a conversational agent that can help users determine the linear model of their specific problem. The authors use prompt engineering to develop two agents that talk to each other and gather information about the user’s problem. They then evaluate how well the generated dialogues match the original problem descriptions. The results show that the dialogues are of good quality, but more work is needed to improve the evaluation metrics. |
Keywords
* Artificial intelligence * Gpt * Prompt
