Ross ROSS = Recommend OSS · open-source software intelligence for agents

OSU-NLP-Group/Mind2Web resource

[NeurIPS'23 Spotlight] "Mind2Web: Towards a Generalist Agent for the Web" -- the first LLM-based web agent and benchmark for generalist web agents observed · 2026-08-28

github.com/OSU-NLP-Group/Mind2Web · homepage · Jupyter Notebook · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

52/100

  • Activity 50
  • Release rhythm 35
  • Longevity 87

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1230
  • days_rel: n/a
  • days_push: 302
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1021 stars · 124 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Mind2Web is the first dataset and benchmark for developing and evaluating generalist LLM-based web agents that follow natural language instructions to complete complex tasks on real-world websites. It contains over 2,000 open-ended tasks from 137 websites across 31 domains, with crowdsourced action sequences, plus fine-tuning code and models for element ranking and action prediction.

Use cases

  • evaluate generalist web agents on real-world websites
  • train LLM-based web navigation agents
  • benchmark element ranking and action prediction on web pages
  • research cross-domain generalization of web agents
  • build agents that follow language instructions on any website
  • compare web agent performance with macro and micro accuracy metrics

When to choose

  • you need a large-scale, diverse benchmark for web agents using real websites rather than simulated ones
  • you want to train or fine-tune models for web task automation from language instructions
  • you need crowdsourced human action sequences as supervision for web navigation research
  • you want paired HTML and screenshot data for multimodal web agent research

When to avoid

  • you need a live interactive online evaluation environment rather than offline traces (see Online-Mind2Web or SeeAct instead)
  • you only target a small set of specific websites or a simulated sandbox environment
  • you need production-ready web automation rather than research benchmarking
  • you cannot access the encrypted test set or agree to data contamination prevention terms

Facets

dataset · maturity active

machine-learning agent-framework rag data-science benchmarking nlp artificial-intelligence large-language-models machine-learning web-development data-science python cross-platform web-agent benchmark llm-agent dataset neurips-2023 web-navigation html-understanding huggingface jupyter-notebook academic-research task-automation element-ranking action-prediction ai-agents natural-language-processing research web-server gpu

2 sources

Member repositories

RepositoryRoleHealth v2
OSU-NLP-Group/Mind2Webmain52

For agents

markdown · JSON · MCP: product_card(name="OSU-NLP-Group/Mind2Web")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem