UXAgent: A System for Simulating Usability Testing of Web Design with LLM Agents
On the map: LLM agents and tool use → GUI and mobile agents
Abstract (arXiv)
Usability testing is a fundamental research method that user experience (UX) researchers use to evaluate and iterate their new designs. But what about evaluating and iterating the usability testing study design itself? Recent advances in Large Language Model-simulated Agent (LLM Agent) research inspired us to design UXAgent to support UX researchers in evaluating and iterating their study design before they conduct the real human-subject study. Our system features a Persona Generator module, an LLM Agent module, and a Universal Browser Connector module to automatically generate thousands of simulated users and to interactively test the target website. The system also provides a Result Viewer Interface so that the UX researchers can easily review and analyze the generated qualitative (e.g., agents' post-study surveys) and quantitative data (e.g., agents' interaction logs), or even interview agents directly. Through a heuristic evaluation with 16 UX researchers, participants praised the innovation of our system but also expressed concerns about the future of LLM Agent usage in UX studies.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Placed in GUI and mobile agents, one of 16 directions in LLM agents and tool use. Builds on 25 of its 96 references that are in the map. First posted on arXiv 13 Apr 2025.
Builds on
25 of 96 references.
References · 25
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
- 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
- 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
- 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,722
- 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,197
- 2023A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesiscited by 350
- 2024LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individualscited by 235
- 2024AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environmentscited by 215
- 2024PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Actioncited by 161
- 2024AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agentscited by 110
- 2023LASER: LLM Agent with State-Space Exploration for Web Navigationcited by 66
- 2024Agents Thinking Fast and Slow: A Talker-Reasoner Architecturecited by 35
13 more
- 2023CollabCoder: A Lower-barrier, Rigorous Workflow for Inductive Collaborative Qualitative Analysis with Large Language Modelscited by 34
- 2023AXNav: Replaying Accessibility Tests from Natural Languagecited by 31
- 2024'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participantscited by 27
- 2025Can LLM Agents Simulate Multi-Turn Human Behavior? Evidence from Real Online Customer Behavior Datacited by 27
- 2025Towards a Design Guideline for RPA Evaluation: A Survey of Large Language Model-Based Role-Playing Agentscited by 22
- 2023An Empathy-Based Sandbox Approach to Bridge the Privacy Gap among Attitudes, Goals, Knowledge, and Behaviorscited by 18
- 2024PersonaFlow: Designing LLM-Simulated Expert Perspectives for Enhanced Research Ideationcited by 16
- 2024Privacy Leakage Overshadowed by Views of AI: A Study on Human Oversight of Privacy in Language Model Agentcited by 14
- 2023Collaboration with Conversational AI Assistants for UX Evaluation: Questions and How to Ask them (Voice vs. Text)cited by 6
- 2023The State of Pilot Study Reporting in Crowdsourcing: A Reflection on Best Practices and Guidelinescited by 5
- 2021Hardhats and Bungaloos: Comparing Crowdsourced Design Feedback with Peer Design Feedback in the Classroomcited by 3
- 2022"Merging Results Is No Easy Task": An International Survey Study of Collaborative Data Analysis Practices Among UX Practitionerscited by 3
- 2025ScreenAudit: Detecting Screen Reader Accessibility Errors in Mobile Apps Using Large Language Modelscited by 2
Built on by
Citing papers per year: 2025: 5; 2026: 5.
10 papers.
- 2025Multi-Agent-as-Judge: Aligning LLM-Agent-Based Automated Evaluation with Multi-Dimensional Human Evaluationcited by 26
- 2025Shop-R1: Rewarding LLMs to Simulate Human Behavior in Online Shopping via Reinforcement Learningcited by 19
- 2025DPRF: A Generalizable Dynamic Persona Refinement Framework for Optimizing Behavior Alignment Between Personalized LLM Role-Playing Agents and Humanscited by 5
- 2025See, Think, Act: Online Shopper Behavior Simulation with VLM Agentscited by 5
- 2025Do MLLMs Capture How Interfaces Guide User Behavior? A Benchmark for Multimodal UI/UX Design Understandingcited by 3
- 2026PerceptUI: LLM Agents as Human-Aligned Synthetic Users for UI/UX Evaluationcited by 1
- 2026UXBench: Measuring the Actionability of LLM-Generated UX Critiquescited by 1
- 2026Personagram: Bridging Personas and Product Design for Creative Ideation with Multimodal LLMscited by 0
- 2026Logarithmic Scores, Power-Law Discoveries: Disentangling Measurement from Coverage in Agent-Based Evaluationcited by 0
- 2026Automatic multimodal UX improvement recommendations from LLM agent user simulationscited by 0
- 2026Automatic multimodal UX improvement recommendations from LLM agent user simulations19 Sep 2026
- 2026UXBench: Measuring the Actionability of LLM-Generated UX Critiques15 Jun 2026
- 2026PerceptUI: LLM Agents as Human-Aligned Synthetic Users for UI/UX Evaluation4 Jun 2026
- 2026Logarithmic Scores, Power-Law Discoveries: Disentangling Measurement from Coverage in Agent-Based Evaluation1 Apr 2026
- 2026Personagram: Bridging Personas and Product Design for Creative Ideation with Multimodal LLMs5 Feb 2026
- 2025See, Think, Act: Online Shopper Behavior Simulation with VLM Agents22 Oct 2025
- 2025DPRF: A Generalizable Dynamic Persona Refinement Framework for Optimizing Behavior Alignment Between Personalized LLM Role-Playing Agents and Humans16 Oct 2025
- 2025Multi-Agent-as-Judge: Aligning LLM-Agent-Based Automated Evaluation with Multi-Dimensional Human Evaluation28 Jul 2025
- 2025Shop-R1: Rewarding LLMs to Simulate Human Behavior in Online Shopping via Reinforcement Learning23 Jul 2025
- 2025Do MLLMs Capture How Interfaces Guide User Behavior? A Benchmark for Multimodal UI/UX Design Understanding8 May 2025
Similar, not cited
Close in wording, no citation either way
- 2025UXAgent: An LLM Agent-Based Usability Testing Framework for Web Design
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- 2026Mapping the Design Space of User Experience for Computer Use Agents
- 2025AgentA/B: Automated and Scalable Web A/BTesting with Interactive LLM Agents
- 2026From SERPs to Agents: A Platform for Comparative Studies of Information Interaction
- 2026UXSim: Towards a Hybrid User Search Simulation
- 2025Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluation