UI2App introduces a benchmark showing that vision-language models can reconstruct web page visuals but largely fail to infer the underlying interaction logic from screenshots alone.
Vision2web: A hierarchical benchmark for visual website development with agent verification
5 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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dataset 2
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2026 5roles
dataset 2representative citing papers
Cookie-Bench is a reference-free 1,000-query web development benchmark paired with Cookie-Frame, a metacognition-inspired three-stage framework (static perception, agent interaction, dynamic scoring) that aligns with human ratings on 13 frontier LLMs.
HTMLCure uses browser-executed interaction trajectories to diagnose and repair LLM HTML outputs, expanding 97K prompts into a 40K refined SFT set that lifts a 27B model to 50.6 on HTMLBench-400 and 81.2 on MiniAppBench.
GLM-5V-Turbo integrates multimodal perception as a core part of reasoning and execution for agentic tasks, reporting strong results in visual tool use and multimodal coding while keeping text-only performance competitive.
The paper develops a unified framework that organizes computer-use agent reliability around perception-decision-execution layers and creation-deployment-operation-maintenance stages to map security and alignment interventions.
citing papers explorer
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UI2App: Benchmarking Visual Interaction Inference in Executable Web Application Generation
UI2App introduces a benchmark showing that vision-language models can reconstruct web page visuals but largely fail to infer the underlying interaction logic from screenshots alone.
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Cookie-Bench: Continuous On-screen Key Interaction Evaluation for Web Generation
Cookie-Bench is a reference-free 1,000-query web development benchmark paired with Cookie-Frame, a metacognition-inspired three-stage framework (static perception, agent interaction, dynamic scoring) that aligns with human ratings on 13 frontier LLMs.
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HTMLCure: Turning Browser Experience into State Guided Repair for Interactive HTML
HTMLCure uses browser-executed interaction trajectories to diagnose and repair LLM HTML outputs, expanding 97K prompts into a 40K refined SFT set that lifts a 27B model to 50.6 on HTMLBench-400 and 81.2 on MiniAppBench.
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GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
GLM-5V-Turbo integrates multimodal perception as a core part of reasoning and execution for agentic tasks, reporting strong results in visual tool use and multimodal coding while keeping text-only performance competitive.
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Securing Computer-Use Agents: A Unified Architecture-Lifecycle Framework for Deployment-Grounded Reliability
The paper develops a unified framework that organizes computer-use agent reliability around perception-decision-execution layers and creation-deployment-operation-maintenance stages to map security and alignment interventions.