mlsanityData to 14 Oct 2026

InfiniteWeb: Scalable Web Environment Synthesis for GUI Agent Training

arXiv 2601.04126 ↗First posted 7 Jan 2026cs.CL cs.AI cs.CVcited by 27

On the map: LLM agents and tool use → Web, search, and research agents

Abstract (arXiv)

GUI agents that interact with graphical interfaces on behalf of users represent a promising direction for practical AI assistants. However, training such agents is hindered by the scarcity of suitable environments. We present InfiniteWeb, a system that automatically generates functional web environments at scale for GUI agent training. While LLMs perform well on generating a single webpage, building a realistic and functional website with many interconnected pages faces challenges. We address these challenges through unified specification, task-centric test-driven development, and a combination of website seed with reference design image to ensure diversity. Our system also generates verifiable task evaluators enabling dense reward signals for reinforcement learning. Experiments show that InfiniteWeb surpasses commercial coding agents at realistic website construction, and GUI agents trained on our generated environments achieve significant performance improvements on OSWorld and Online-Mind2Web, demonstrating the effectiveness of proposed system.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 20 of its 34 references that are in the map. First posted on arXiv 7 Jan 2026.

Builds on

20 of 34 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025An Illusion of Progress? Assessing the Current State of Web Agents2 Apr
  2. 2024AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials12 Dec
  3. 2023Mind2Web: Towards a Generalist Agent for the Web9 Jun

Other references · 17

  1. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
  2. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  3. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
  4. 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,195
  5. 2023CogAgent: A Visual Language Model for GUI Agentscited by 704
  6. 2019Leveraging Procedural Generation to Benchmark Reinforcement Learningcited by 483
  7. 2022CodeT: Code Generation with Generated Testscited by 384
  8. 2018Reinforcement Learning on Web Interfaces Using Workflow-Guided Explorationcited by 284
  9. 2025ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Usecited by 254
  10. 2024OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesiscited by 163
  11. 2025Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agentscited by 159
  12. 2024Design2Code: Benchmarking Multimodal Code Generation for Automated Front-End Engineeringcited by 152
5 more
  1. 2025WebGen-Bench: Evaluating LLMs on Generating Interactive and Functional Websites from Scratchcited by 72
  2. 2025MobileWorld: Benchmarking Autonomous Mobile Agents in Agent-User Interactive and MCP-Augmented Environmentscited by 72
  3. 2025MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agentscited by 67
  4. 2025AgentSynth: Scalable Task Generation for Generalist Computer-Use Agentscited by 46
  5. 2025UI-E2I-Synth: Advancing GUI Grounding with Large-Scale Instruction Synthesiscited by 20

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 27.

27 papers.

Sort:

By area:

  1. 2026Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligencecited by 54
  2. 2026Qwen-AgentWorld: Language World Models for General Agentscited by 28
  3. 2026CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agentscited by 23
  4. 2026AutoWebWorld: Synthesizing Infinite Verifiable Web Environments via Finite State Machinescited by 21
  5. 2026Recursive Synthesis for Long-Horizon Terminal Taskscited by 19
  6. 2026Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?cited by 18
  7. 2026MobileGym: A Verifiable and Highly Parallel Simulation Platform for Mobile GUI Agent Researchcited by 13
  8. 2026SPADE: Self-Play in Adaptive Synthetic Executable Environmentscited by 12
  9. 2026UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experiencecited by 11
  10. 2026OpenComputer: Verifiable Software Worlds for Computer-Use Agentscited by 10
  11. 2026Autonomous Research Agents: A Survey of AI Scientists and the Verification Gapcited by 9
  12. 2026Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesiscited by 8
15 more
  1. 2026Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Applicationcited by 8
  2. 2026Qwen-CUA: Native Computer Use for (almost) Everythingcited by 8
  3. 2026SWE-AGILE: A Software Agent Framework for Efficiently Managing Dynamic Reasoning Contextcited by 6
  4. 2026PhoneBuddy: Training Open Models for Agentic Phone Usecited by 4
  5. 2026Scalable Environments Drive Generalizable Agentscited by 2
  6. 2026Echoverse: Deep, Evolving Environments for Training Computer-Use Agents at Scalecited by 2
  7. 2026CUA-Universe: A Scalable and Dynamic Environment for Hybrid GUI+CLI Agentscited by 2
  8. 2026PhoneWorld: From Real-App Trajectories to Dynamic and Verifiable Environments for Phone-Use Agentscited by 1
  9. 2026UI-Mate: Advancing Open-Weight Foundation GUI Agents with In-Context Demonstrationscited by 1
  10. 2026RecreationWorld: Scalable and Verifiable Environments for Hybrid Computer-Use Agentscited by 1
  11. 2026From Trajectories to Grounded Preferences: Process Preference Synthesis via Interaction Element Graphs for Web PRMscited by 0
  12. 2026CompoWorld: Compositional Environment Scaling for General Agentscited by 0
  13. 2026WEFT: Scaling Tool-Use Post-Training for General-Purpose Agentscited by 0
  14. 2026AutoGUIWorld: Image Generators as Visual World Models for GUI Agentcited by 0
  15. 2026AutoEnvScaling: Automating the Data Flywheel with Terminal Agentscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026ScaleWoB: Guiding GUI Agents with Coding Agents via Large-Scale Environmental Synthesis
  2. 2026WebFactory: Automated Compression of Foundational Language Intelligence into Grounded Web Agents
  3. 2026GUI-GENESIS: Automated Synthesis of Efficient Environments with Verifiable Rewards for GUI Agent Post-Training
  4. 2026WebGym: Scaling Training Environments for Visual Web Agents with Realistic Tasks
  5. 2026Safe and Scalable Web Agent Learning via Recreated Websites
  6. 2026Training Needs Trustworthy Worlds: Verified Synthetic Web Environments for Agent Learning
  7. 2025WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning
  8. 2025WEBSERV: A Full-Stack and RL-Ready Web Environment for Training Web Agents at Scale