RRepoGEO

REPOGEO REPORT · LITE

opendilab/awesome-RLHF

Default branch main · commit 96acdd45 · scanned 5/24/2026, 4:23:34 AM

GitHub: 4,371 stars · 253 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface opendilab/awesome-RLHF, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README opening to emphasize its role as a central discovery hub

    Why:

    CURRENT
    This is a collection of research papers for **Reinforcement Learning with Human Feedback** (RLHF).
    COPY-PASTE FIX
    This is the **definitive, continually updated curated index and central hub** for essential research papers, codebases, datasets, and blogs on **Reinforcement Learning with Human Feedback** (RLHF). It serves as your primary starting point for exploring the RLHF landscape.
  • mediumhomepage#2
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    https://github.com/opendilab/awesome-RLHF
  • mediumtopics#3
    Add 'awesome-list' to repository topics

    Why:

    CURRENT
    deep-learning, deep-reinforcement-learning, human-feedback, large-language-models, reinforcement-learning, rlhf
    COPY-PASTE FIX
    deep-learning, deep-reinforcement-learning, human-feedback, large-language-models, reinforcement-learning, rlhf, awesome-list

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface opendilab/awesome-RLHF
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face's Alignment Handbook
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face's Alignment Handbook · recommended 1×
  2. OpenAI's Research Papers and Blog Posts · recommended 1×
  3. DeepMind's Research Papers · recommended 1×
  4. Stanford's CS324 (Large Language Models) Course Materials · recommended 1×
  5. Anthropic's 'Constitutional AI' Paper and Blog Posts · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive resources on reinforcement learning with human feedback?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face's Alignment Handbook
    2. OpenAI's Research Papers and Blog Posts
    3. DeepMind's Research Papers
    4. Stanford's CS324 (Large Language Models) Course Materials
    5. Anthropic's 'Constitutional AI' Paper and Blog Posts
    6. Carnegie Mellon University (CMU) LTI Research
    7. Microsoft Research Papers

    AI recommended 7 alternatives but never named opendilab/awesome-RLHF. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the essential papers and codebases for implementing RLHF in large language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face TRL (huggingface/trl)
    2. DeepSpeed-Chat (microsoft/DeepSpeed)
    3. trlX (CarperAI/trlx)
    4. OpenAI's Baselines (openai/baselines)
    5. Anthropic's Constitutional AI codebase

    AI recommended 5 alternatives but never named opendilab/awesome-RLHF. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of opendilab/awesome-RLHF?
    pass
    AI named opendilab/awesome-RLHF explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts opendilab/awesome-RLHF in production, what risks or prerequisites should they evaluate first?
    pass
    AI named opendilab/awesome-RLHF explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo opendilab/awesome-RLHF solve, and who is the primary audience?
    pass
    AI named opendilab/awesome-RLHF explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of opendilab/awesome-RLHF. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/opendilab/awesome-RLHF.svg)](https://repogeo.com/en/r/opendilab/awesome-RLHF)
HTML
<a href="https://repogeo.com/en/r/opendilab/awesome-RLHF"><img src="https://repogeo.com/badge/opendilab/awesome-RLHF.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

opendilab/awesome-RLHF — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite