web-agent
webagentswebchain
WebChain v2
A large-scale, human-annotated dataset of real-world web interaction trajectories for training and evaluating web agents.
[Paper] [Code] [Dataset]
WebChain captures how people complete real tasks on live websites. It is designed for agents that must both identify the correct interface element and reason through a sequence of actions. Each trajectory aligns screenshots, web structure, grounded actions, and reasoning signals instead of treating web navigation as… See the full description on the dataset page: https://huggingface.co/datasets/webagentlab/webchain.webchain-legacy
WebChain
WebChain is a large-scale, human-annotated dataset of real-world web interaction trajectories for training and evaluating GUI agents and web agents. WebChain contains 31,725 trajectories, 317,993 steps, and 428 unique domains. Its core contribution is a Triple Alignment of visual context, structural context, and action grounding, enabling supervision for both spatial grounding and long-horizon planning.
Paper: https://arxiv.org/abs/2603.05295
Open access… See the full description on the dataset page: https://huggingface.co/datasets/webagentlab/webchain-legacy.ai-research-berkeley-webagent
Berkeley WebAgent Experiment Artifacts
Native GEPA, CLUE and ACE experiment logs and available actor trajectory evidence.
Files require manual access approval. Request access with your Hugging Face account.
Results and complete evidence snapshot — September 23, 2026
Combined experiment summary: GEPA, CLUE and ACE; method × site for WebArena.
Non-WebArena repeat scores and variance, including completed ACE ≤50k-token evaluations.
WebArena / GoBrowse progress and… See the full description on the dataset page: https://huggingface.co/datasets/MinjaeLee-FuriosaAI-Ext/ai-research-berkeley-webagent.agent-web-index
Agent Web Index — how much of the web can AI assistants actually read?
50,413 domains measured live. 26% of them cannot be read by at least one of
ChatGPT, Claude, Perplexity or Gemini. Updated daily. Live index: https://shop.lumnika.com/ai-readiness/
Every row here is the result of real HTTP requests, not an estimate and not a re-publication of
someone else's crawl: each domain's homepage is requested once as a browser and once as each of the
published AI crawler user-agents… See the full description on the dataset page: https://huggingface.co/datasets/DeusHorizon/agent-web-index.AFM-WebAgent-RL-Dataset
Data Introduction
This dataset serves as the core training data for Agent Foundation Models (AFMs), specifically designed to elicit end-to-end multi-agent reasoning capabilities in large language models. Built on the novel "Chain-of-Agents (CoA)" paradigm, the dataset leverages a multi-agent distillation framework to transform collaboration processes from state-of-the-art multi-agent systems into trajectory data suitable for supervised fine-tuning (SFT), simulating dynamic… See the full description on the dataset page: https://huggingface.co/datasets/PersonalAILab/AFM-WebAgent-RL-Dataset.