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DOI: 10.4121/d34aa48b-9722-4ad4-b108-a62878c1feca

He, Gaole; Demartini, Gianluca; Gadiraju, Ujwal (2025): User Interaction Dataset for CHI 2025 paper "Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant.". Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/d34aa48b-9722-4ad4-b108-a62878c1feca.v1

Categories

• Artificial Intelligence and Image Processing
• Information and Computing Sciences

Keywords

Daily Assistant Human-AI Collaboration Large Language Models LLM agents User Trust

Licence

CC BY 4.0

Interoperability

• RO-Crate Metadata

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by Gaole He , Gianluca Demartini , Ujwal Gadiraju

This repo contains all code, data, and user interfaces associated with paper "Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant." In our study, we analyzed different extents of user involvement in the planning and execution stages of LLM agents. Our data is evaluated based on action sequences. We also recorded how users interact with LLM agents and provided an interface built upon Flask.

History

• 2025-02-06 first online, published, posted

Publisher

4TU.ResearchData

Format

table/csv, text/txt

Associated peer-reviewed publication

Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant.

References

• https://arxiv.org/abs/2502.01390

Code hosting project url

https://github.com/RichardHGL/CHI2025_Plan-then-Execute_LLMAgent

Same as

https://github.com/RichardHGL/CHI2025_Plan-then-Execute_LLMAgent/tree/main/data_analysis/anonymized_data

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Software Technology, Web Information Systems Group