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How to use Awesome AI Scientist: what you can do with it

A curated GitHub list of papers, AI Scientist systems, benchmarks, datasets and open-source platforms for AI that does science.

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Authorization notice. This tool is dual-use. Only use it on software, sites and systems you own or have explicit permission to test, and follow the relevant licenses and terms of service.

What do you want to do?

4 use cases

  • Run an open AI Scientist system on a test question

    Pick a linked end-to-end system and run it on one small research question.

    View prompt
    Using the README of Omni-Scientist/Awesome-AI-Scientist, list the End-to-End AI Scientists entries that link to a GitHub repository and fit the research question <research question>. Return each system name, its paper link and its repository link, and confirm each repository link appears in the README before reporting it.

  • Shortlist benchmarks to test a science agent

    Pick benchmarks and leaderboards that fit the science task your agent handles.

    View prompt
    Using the README of Omni-Scientist/Awesome-AI-Scientist, find the Benchmarks & Evaluation entries that match <science task>. For each match, give the name, paper link and any leaderboard listed in the Leaderboards & Live Trackers section, and state one scoring detail from the paper.

  • Find datasets and environments for a science agent

    Locate datasets, corpora and environments to train or test an agent on science tasks.

    View prompt
    Using the README of Omni-Scientist/Awesome-AI-Scientist, list the Datasets, Corpora & Environments entries relevant to <scientific field>. Return each name and link, and verify on each linked page that the access terms are stated before you include it.

  • Review safety and policy readings for autonomous research

    Collect the safety, ethics and policy sources on AI systems that run research.

    View prompt
    Using the README of Omni-Scientist/Awesome-AI-Scientist, pick five entries from the Safety, Ethics & Policy section that relate to <use case>. Return each title, link and a one-sentence note on the risk it covers, and check that each note matches the linked paper's abstract.

Quick start with Awesome AI Scientist

  1. Check you have what it needs: A web browser to read the README and follow GitHub links; A GitHub account if you plan to clone or fork a linked repository; A Python environment for running any linked project (the list is tagged Python).
  2. Open Omni-Scientist/Awesome-AI-Scientist on GitHub and read the README and license.
  3. Open the End-to-End AI Scientists section of the README.
  4. Pick an entry whose badge links to a GitHub repository, such as The AI Scientist or data-to-paper.
  5. Open that repository and read its own README, because this list does not give setup steps.
  6. Clone the chosen repository with git and create a Python environment for it. (inferred, check the README)

These steps come from our top use case, Run an open AI Scientist system on a test question, which also has a copy-paste agent prompt.

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About this repo

Requirements

  • A web browser to read the README and follow GitHub links
  • A GitHub account if you plan to clone or fork a linked repository
  • A Python environment for running any linked project (the list is tagged Python)
  • Time to read each linked project's own README, since this list does not contain install instructions

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Questions about Awesome AI Scientist

What is Awesome AI Scientist?

A curated GitHub list of papers, AI Scientist systems, benchmarks, datasets and open-source platforms for AI that does science. It is an open-source project on GitHub: https://github.com/Omni-Scientist/Awesome-AI-Scientist.

Who is Awesome AI Scientist for?

Written for researchers and engineers who want to find an AI Scientist system, benchmark or dataset to study or try.

What can I do with Awesome AI Scientist?

4 use cases so far, for example: Run an open AI Scientist system on a test question; Shortlist benchmarks to test a science agent; Find datasets and environments for a science agent. Each has steps and a copy-paste agent prompt.

What do I need to run Awesome AI Scientist?

A web browser to read the README and follow GitHub links; A GitHub account if you plan to clone or fork a linked repository; A Python environment for running any linked project (the list is tagged Python); Time to read each linked project's own README, since this list does not contain install instructions.

What are alternatives to Awesome AI Scientist?

Other hot AI repos in Research: Trustworthy Agent Simulation, Kaas, By2 KB, Md2 HD, Loci.

Is Awesome AI Scientist safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.