DEDUPED Hot AI repos, turned into use cases Get 5 a day

What you can do with Awesome Rsi

Awesome RSI is a curated, community-maintained reading list of research on recursive self-improvement in AI, organized by model-level, harness-level, embodied, and safety topics.

Trended earlier

lobehub/awesome-rsi on GitHub

Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk.

What do you want to do?

4 use cases

  • Build a staged reading path on recursive self-improvement

    Turn the list's fundamentals and surveys into an ordered reading plan for a new team member.

    View prompt
    Using the awesome-rsi README at lobehub/awesome-rsi, build an ordered reading path of about 10 papers for a reader focused on <focus area>. Start from Fundamentals & Getting Started, then pick entries from the section that matches the focus. Output a numbered list with one sentence per paper. Verify that every title and link appears in the README exactly as written.

  • Check RSI claims against the list's three evidence levels

    Sort a set of self-improvement papers by task gain, retained gain, or improver gain.

    View prompt
    Using the awesome-rsi README at lobehub/awesome-rsi as the source of definitions, classify the papers named in <paper list> as task gain, retained gain, or improver gain. Output a table with columns for paper title, evidence level, and missing evidence. Verify that each classification is supported by the paper's own abstract, not only by its README summary.

  • Pick benchmarks for testing a self-improving agent

    Shortlist RSI-specific and proxy benchmarks from the list to test an agent you are building.

    View prompt
    Using the Benchmarks & Evaluations section of the awesome-rsi README at lobehub/awesome-rsi, shortlist three to five benchmarks for an agent that updates its <update target>. Label each as direct RSI evaluation or capability proxy and give one reason per choice. Verify that every benchmark name and link is copied from the README.

  • Scout open frameworks for self-evolving agent harnesses

    Find frameworks in the list that evolve memory, skills, or harness code for an agent.

    View prompt
    Using the Frameworks & Tools section of the awesome-rsi README at lobehub/awesome-rsi, shortlist two or three frameworks that evolve <update target> for an agent. For each one, output its name, the README category it sits under, and what its README entry says it does. Verify that no install command or feature is claimed unless the framework's own project page states it.

How to use Awesome Rsi

  1. Check you have what it needs: A web browser to open the GitHub README and the linked arXiv or journal pages; Optional: a note-taking file or spreadsheet to track papers and their evidence levels.
  2. Open lobehub/awesome-rsi on GitHub and read the README and license.
  3. Open the Fundamentals & Getting Started section of the README and read the opening note that says to start there.
  4. Read the Scope & Terminology section and write down the definitions of self-refinement, persistent self-improvement, and recursive self-improvement.
  5. Pick two or three surveys from Fundamentals & Getting Started, such as the Recursive Self-Improvement in AI survey and the Safety in Self-Evolving Agents survey.
  6. Choose one section that matches your focus, such as Model-level RSI, Harness-level RSI, or Embodied & Physical Self-Improvement, and read its intro paragraph.

These steps come from our top use case, Build a staged reading path on recursive self-improvement, which also has a copy-paste agent prompt.

Awesome Rsi alternatives · Best AI repos for Research

About this repo

  • Who it is forResearchers, students, and AI agents who need an organized map of recursive self-improvement papers, surveys, and benchmarks before choosing what to read, test, or build on.
  • Why it is hot
  • Sourcegithub.com/lobehub/awesome-rsi · Back to Hot repos

Requirements

  • A web browser to open the GitHub README and the linked arXiv or journal pages
  • Optional: a note-taking file or spreadsheet to track papers and their evidence levels
Maintain Awesome Rsi? Add the Featured on Deduped badge

Paste this into your README:

[![Featured on Deduped](https://dedupedai.com/badge/lobehub-awesome-rsi.svg)](https://dedupedai.com/use-cases/lobehub-awesome-rsi/?ref=badge)

More badge styles and HTML

Questions about Awesome Rsi

What is Awesome Rsi?

Awesome RSI is a curated, community-maintained reading list of research on recursive self-improvement in AI, organized by model-level, harness-level, embodied, and safety topics. It is an open-source project on GitHub: https://github.com/lobehub/awesome-rsi.

Who is Awesome Rsi for?

Researchers, students, and AI agents who need an organized map of recursive self-improvement papers, surveys, and benchmarks before choosing what to read, test, or build on.

What can I do with Awesome Rsi?

4 use cases so far, for example: Build a staged reading path on recursive self-improvement; Check RSI claims against the list's three evidence levels; Pick benchmarks for testing a self-improving agent. Each has steps and a copy-paste agent prompt.

What do I need to run Awesome Rsi?

A web browser to open the GitHub README and the linked arXiv or journal pages; Optional: a note-taking file or spreadsheet to track papers and their evidence levels.

What are alternatives to Awesome Rsi?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is Awesome Rsi 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.