WaitGPT: Monitoring and Steering Conversational LLM Agent in Data Analysis with On-the-Fly Code Visualization
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
Large language models (LLMs) support data analysis through conversational user interfaces, as exemplified in OpenAI's ChatGPT (formally known as Advanced Data Analysis or Code Interpreter). Essentially, LLMs produce code for accomplishing diverse analysis tasks. However, presenting raw code can obscure the logic and hinder user verification. To empower users with enhanced comprehension and augmented control over analysis conducted by LLMs, we propose a novel approach to transform LLM-generated code into an interactive visual representation. In the approach, users are provided with a clear, step-by-step visualization of the LLM-generated code in real time, allowing them to understand, verify, and modify individual data operations in the analysis. Our design decisions are informed by a formative study (N=8) probing into user practice and challenges. We further developed a prototype named WaitGPT and conducted a user study (N=12) to evaluate its usability and effectiveness. The findings from the user study reveal that WaitGPT facilitates monitoring and steering of data analysis performed by LLMs, enabling participants to enhance error detection and increase their overall confidence in the results.
Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 37 of its 78 references that are in the map. First posted on arXiv 3 Aug 2024.
Builds on
37 of 78 references.
References · 37
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- 2023Beyond Generating Code: Evaluating GPT on a Data Visualization Coursecited by 16
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- 2023CrossData: Leveraging Text-Data Connections for Authoring Data Documentscited by 6
- 2022Smallset Timelines: A Visual Representation of Data Preprocessing Decisionscited by 4
- 2022Visualizing the Scripts of Data Wrangling with SOMNUScited by 4
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Citing papers per year: 2024: 1; 2025: 19; 2026: 18.
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