AboutAI
arXiv cs.AI
  • Score 90
  • Official

WebAnything: From the Wild Web to Scalable Agent Environments

arXiv:2610.37786v1 Announce Type: new Abstract: Web agents require diverse, executable, and resettable website environments for reproducible training and evaluation. Human-assisted mirrors demand per-site engineering, while generative construction can diverge from specified real websites. Capture-and-replay preserves observations, with interaction coverage constrained by captured content and repla

So what

What this event means by reading role—not a longer recap.

  • BuilderBuilders can use the released framework and code to generate resettable web environments for agent training without per-site manual engineering.
  • ResearcherFine-tuning Qwen3.5-9B on 5,856 WebAnything trajectories improved REAL success by 9.9 points and WebArena-Verified success by 13.33 points.
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Score dimensions

Higher total means read first. Each bar is one factor we use to rank the system pool. How we score

RelevanceHow tightly this is about AI.
82
ImpactHow much this could change the field or the market.
70
NoveltyHow new this is versus a recap.
75
CredibilityHow much we trust the source.
97
ActionabilityWhether a reader can do something with it.
65