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WebAnything paper proposes scalable web environments for training and evaluating web agents

This story is from 2026-10-30. It is preserved in the archive; the latest stories are on the live feed.

A new arXiv paper, WebAnything, addresses the need for diverse, executable, and resettable website environments that enable reproducible training and evaluation of web agents, noting human-assisted mirrors are costly.

Read the full story at arXiv cs.AI ↗

Timeline · 1 report

  1. 2026-10-30 04:00 · arXiv cs.AI
    WebAnything: From the Wild Web to Scalable Agent Environments

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