WebSight: A Vision-First Architecture for Robust Web Agents

Tanvir Bhathal; Asanshay Gupta

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arXiv · 2508.16987

WebSight: A Vision-First Architecture for Robust Web Agents

Tanvir Bhathal·Asanshay Gupta

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Abstract

We introduce WebSight, a vision-based autonomous web agent, designed to interact with web environments purely through visual perception, eliminating dependence on HTML or DOM-based inputs. Central to our approach we introduce our new model, WebSight-7B, a fine-tuned vision-language model optimized for UI element interaction, trained using LoRA on a web-focused subset of the Wave-UI-25K dataset. WebSight integrates this model into a modular multi-agent architecture, comprising planning, reasoning, vision-action, and verification agents, coordinated through an episodic memory mechanism. WebSight-7B achieves a top-1 accuracy of 58.84% on the Showdown Clicks benchmark, outperforming several larger generalist models while maintaining lower latency. The full WebSight agent achieves a 68.0% success rate on the WebVoyager benchmark, surpassing systems from labs such as OpenAI (61.0%) and HCompany (Runner H, 67.0%). Among tasks completed, WebSight answers correctly 97.14% of the time, indicating high precision. Together, WebSight and WebSight-7B establish a new standard for interpretable, robust, and efficient visual web navigation.

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Tanvir Bhathal, Asanshay Gupta. 2025-08-23. WebSight: A Vision-First Architecture for Robust Web Agents. https://arxiv.org/abs/2508.16987

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