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<aside> <img src="/icons/verified_green.svg" alt="/icons/verified_green.svg" width="40px" /> About PAPER


This channel is dedicated to building and expanding a comprehensive paper database focused on the Web Agent field and the boarder GUI agent field. Let’s collaborate to enrich this database and advance research in the exciting world of web agents!

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🔥 Newly updated(May)

New~ May 30 |ZeroGUI: Automating Online GUI Learning at Zero Human Cost

New~ May 29 |Grounded Reinforcement Learning for Visual Reasoning

New~ May 28 |UI-Evol: Automatic Knowledge Evolving for Computer Use Agents

New~ May 28 |RedTeamCUA: Realistic Adversarial Testing of Computer-Use Agents in Hybrid Web-OS Environments

New~ May 28 |WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning

New~ May 27 |BacktrackAgent: Enhancing GUI Agent with Error Detection and Backtracking Mechanism

New~ May 27 |AdInject: Real-World Black-Box Attacks on Web Agents via Advertising Delivery

New~ May 27 |UI-Genie: A Self-Improving Approach for Iteratively Boosting MLLM-based Mobile GUI Agents

New~ May 26 |WebCoT: Enhancing Web Agent Reasoning by Reconstructing Chain-of-Thought in Reflection, Branching, and Rollback

New~ May 26 |ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows

May 23 |TransBench: Breaking Barriers for Transferable Graphical User Interface Agents in Dynamic Digital Environments

May 23 |Think or Not? Selective Reasoning via Reinforcement Learning for Vision-Language Models

May 23 |ProgRM: Build Better GUI Agents with Progress Rewards

May 22 |GUI-explorer: Autonomous Exploration and Mining of Transition-aware Knowledge for GUI Agent

May 22 |ARPO:End-to-End Policy Optimization for GUI Agents with Experience Replay

May 22 |WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning

May 22 |GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents

May 21 |ReGUIDE: Data Efficient GUI Grounding via Spatial Reasoning and Search

May 20 |Iterative Tool Usage Exploration for Multimodal Agents via Step-wise Preference Tuning

May 20 |Building a Stable Planner: An Extended Finite State Machine Based Planning Module for Mobile GUI Agent

May 20 |From Assistants to Adversaries: Exploring the Security Risks of Mobile LLM Agents

May 20 |Efficient Agent Training for Computer Use

May 20 |Hidden Ghost Hand: Unveiling Backdoor Vulnerabilities in MLLM-Powered Mobile GUI Agents

May 20 |EVA: Red-Teaming GUI Agents via Evolving Indirect Prompt Injection

May 19 |Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis

May 19 |GEM: Gaussian Embedding Modeling for Out-of-Distribution Detection in GUI Agents

May 19 |Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents

May 18 |Enhancing Visual Grounding for GUI Agents via Self-Evolutionary Reinforcement Learning

May 18 |Enhance Mobile Agents Thinking Process Via Iterative Preference Learning

May 18 |UIShift: Enhancing VLM-based GUI Agents through Self-supervised Reinforcement Learning

May 17 |Mobile-Bench-v2: A More Realistic and Comprehensive Benchmark for VLM-based Mobile Agents

May 16 |Group-in-Group Policy Optimization for LLM Agent Training

May 16 |A Survey on the Safety and Security Threats of Computer-Using Agents: JARVIS or Ultron?

May 15 |LLM-Explorer: Towards Efficient and Affordable LLM-based Exploration for Mobile Apps

May 15 |AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenge

May 12 |Web-Bench: A LLM Code Benchmark Based on Web Standards and Frameworks

May 11 |Seed1.5-VL Technical Report

May 11 |Web Page Classification using LLMs for Crawling Support

May 06 |OSUniverse: Benchmark for Multimodal GUI-navigation AI Agents

May 01 |ScaleTrack: Scaling and back-tracking Automated GUI Agents

May 01 |[Visual Test-time Scaling for GUI Agent Grounding ](https://webagentlab.notion.site/Visual-Test-time-Scaling-for-GUI-Agent-Grounding-1ebcc62ec9f1805bb890cdc5711cbc25)

May 01 |Towards Efficient Online Tuning of VLM Agents via Counterfactual Soft Reinforcement Learning

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