REPOGEO REPORT · LITE
lasgroup/SDPO
Default branch main · commit c52586ba · scanned 6/4/2026, 5:48:35 PM
GitHub: 923 stars · 101 forks
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 lasgroup/SDPO, 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.
- highabout#1Clarify the 'About' description to disambiguate SDPO
Why:
CURRENTReinforcement Learning via Self-Distillation (SDPO)
COPY-PASTE FIXSelf-Distilled Policy Optimization (SDPO): Reinforcement Learning with Rich Feedback for LLMs
- hightopics#2Add more specific topics to improve category visibility
Why:
CURRENTdistillation, llm, reasoning, rl
COPY-PASTE FIXdistillation, llm, reasoning, rl, rich-feedback, credit-assignment, policy-optimization, self-distillation-rl
- mediumreadme#3Update README H1 to include key differentiators
Why:
CURRENT# Reinforcement Learning via Self-Distillation (SDPO)
COPY-PASTE FIX# Self-Distilled Policy Optimization (SDPO): Reinforcement Learning with Rich Feedback for LLMs
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.
- OpenAI's API · recommended 2×
- Hugging Face Transformers · recommended 2×
- TRLX · recommended 1×
- 🤗 Transformers · recommended 1×
- LangChain · recommended 1×
- CATEGORY QUERYHow to improve credit assignment in reinforcement learning for LLMs using rich textual feedback?you: not recommendedAI recommended (in order):
- OpenAI's API
- TRLX
- 🤗 Transformers
- Hugging Face Transformers
- LangChain
- LlamaIndex
- Argilla
- Anthropic's Claude API
- OpenAI's GPT-4
- Llama 3
- ESLint
- Pylint
- Gradio
- Streamlit
AI recommended 14 alternatives but never named lasgroup/SDPO. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat techniques use self-distillation to enhance reinforcement learning for large language models?you: not recommendedAI recommended (in order):
- Hugging Face Transformers
- trl
- DeepMind's AlphaCode/AlphaGo-like architectures
- Anthropic's Constitutional AI
- RLAIF (Reinforcement Learning from AI Feedback)
- Hugging Face `transformers`
- accelerate
- DistilBERT
- TinyLlama
- OpenAI's API
- OpenAssistant
- Llama 2 70B
- Llama 2 7B
- Google's Self-Instruct
- Stable Baselines3
AI recommended 15 alternatives but never named lasgroup/SDPO. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
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 lasgroup/SDPO?passAI named lasgroup/SDPO explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts lasgroup/SDPO in production, what risks or prerequisites should they evaluate first?passAI named lasgroup/SDPO 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 lasgroup/SDPO solve, and who is the primary audience?passAI named lasgroup/SDPO explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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lasgroup/SDPO — 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