# "Zooming In" on Agentic Web Browsers as Assistive Technologies: A Case Study with a Low-Vision Technology Expert

arXiv: https://arxiv.org/abs/2606.24870 · HTML: https://mlsanity.com/paper/2606.24870/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in GUI and mobile agents, one of 16 directions in LLM agents and tool use.
- Builds on 3 of its 6 references that are in the map.
- First posted on arXiv 23 Jun 2026.

## Placed in

- LLM agents and tool use / [GUI and mobile agents](https://mlsanity.com/agents/gui-and-mobile-agents/)

## Builds on (most cited first, 3 of 3)

- [Mapping the Design Space of User Experience for Computer Use Agents](https://mlsanity.com/paper/2602.07283/) (2026)
- [A11y-CUA Dataset: Characterizing the Accessibility Gap in Computer Use Agents](https://mlsanity.com/paper/2602.09310/) (2026)
- [Task Mode: Dynamic Filtering for Task-Specific Web Navigation using LLMs](https://mlsanity.com/paper/2507.14769/) (2025)

## Abstract (arXiv)

Agentic Web Browsers (AWBs), powered by Large Language Models (LLMs), are emerging as autonomous systems capable of navigating the Web on behalf of users. Beyond enhancing productivity, they could also offer significant promise as Assistive Technologies (ATs) for visually-impaired individuals, transforming web interaction into a fluid conversational exchange. In this paper, we present a case study with a low-vision technology expert, examining how AWBs can support visually-impaired users in web navigation. The findings show that, despite the current limitations, the navigation experience is notably fluid and flexible, underscoring the strong potential of AWBs to enhance accessibility and reduce barriers in web interaction, with implications that may extend beyond accessibility to agentic UX more broadly.