← all repositories
reacher-z/Awesome-CUA

An awesome list that actually checks its sources

Awesome-CUA catalogs computer-use agent research with every entry reviewed against a first-party source — plus machine-readable JSONL and SQLite you can feed to RAG.

★605 stars Python LearningAgents
Awesome-CUA
Collecting fresh signals — velocity needs a few days of history.
collecting data…
star history

What it does It’s a curated catalog of everything around computer-use agents: 1,673 reviewed papers and surveys, plus datasets, benchmarks, models, frameworks, and tools — 2,170 curated resources total. Coverage spans web, desktop, Android, iOS, and even HarmonyOS, organized by topic (grounding, planning, memory, RL, safety) and by platform. There’s a searchable website, but the whole catalog also ships as JSONL/SQLite and RAG-ready documents, with an llms.txt for language-model navigation.

The interesting bit Most awesome lists are link dumps with a shelf life. This one grades its own entries: curated records were checked against a first-party source snapshot, awaiting-review records have verified bibliographic metadata, and 2,062 discovered candidates sit in a queue awaiting resolution. It also tracks which code, datasets, and models are actually connected to which papers through primary evidence — the boring provenance work that makes the list trustworthy.

Key highlights

  • 1,673 reviewed papers and surveys, grouped by topic and year, with original sources linked
  • 86 datasets, 91 benchmarks, 98 model releases, 87 frameworks, 49 open agent implementations
  • Machine-readable exports: JSONL, SQLite, RAG documents, and llms.txt for LLM consumption
  • Local search via a dependency-free Python script (3.11+), no install required
  • Also published as a Hugging Face dataset (TIGER-Lab/AwesomeCUA)

Caveats

  • 451 records are still awaiting full review, and 2,062 candidates unresolved — the catalog is honest about being a work in progress
  • The learning-resources section is thin: two courses/tutorials

Verdict Anyone doing GUI-agent research or building a computer-use agent should bookmark this — it’s the map of the field. If you just want a quickstart tutorial, look elsewhere (there are literally two).

Frequently asked

What is reacher-z/Awesome-CUA?
Awesome-CUA catalogs computer-use agent research with every entry reviewed against a first-party source — plus machine-readable JSONL and SQLite you can feed to RAG.
Is Awesome-CUA open source?
Yes — reacher-z/Awesome-CUA is an open-source project tracked on heatdrop.
What language is Awesome-CUA written in?
reacher-z/Awesome-CUA is primarily written in Python.
How popular is Awesome-CUA?
reacher-z/Awesome-CUA has 605 stars on GitHub.
Where can I find Awesome-CUA?
reacher-z/Awesome-CUA is on GitHub at https://github.com/reacher-z/Awesome-CUA.

heatdrop uses Google Analytics to see which pages get read — nothing else. Your call. How we handle data.