REPOGEO REPORT · LITE
EvolvingLMMs-Lab/open-r1-multimodal
Default branch main · commit 232b7ba8 · scanned 5/26/2026, 2:02:57 AM
GitHub: 1,550 stars · 72 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 EvolvingLMMs-Lab/open-r1-multimodal, 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.
- hightopics#1Add specific topics for multimodal RLHF and math reasoning
Why:
COPY-PASTE FIXmultimodal-llm, rlhf, vision-language-models, math-reasoning, reinforcement-learning, deep-learning, transformers, qwen2-vl
- highreadme#2Clarify the README's opening paragraph to state the problem solved
Why:
CURRENTWe conducted a speed-run on to investigate R1's paradigm in multimodal models after observing growing interest in R1 and studying the elegant implementation of the GRPO algorithm in `open-r1` and `trl`.
COPY-PASTE FIXThis repository extends the `open-r1` paradigm to enable multimodal large language model (VLM) training with Reinforcement Learning from Human Feedback (RLHF). It provides an implementation for integrating VLMs like Qwen2-VL, alongside open-sourced 8k multimodal RL training examples focused on math reasoning and pre-trained GRPO models, primarily for AI researchers and developers.
- mediumhomepage#3Add a homepage URL to the repository
Why:
COPY-PASTE FIXhttps://github.com/EvolvingLMMs-Lab/open-r1-multimodal
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.
- ray-project/ray · recommended 3×
- huggingface/transformers · recommended 2×
- huggingface/trl · recommended 2×
- huggingface/peft · recommended 1×
- huggingface/alignment-handbook · recommended 1×
- CATEGORY QUERYHow to train multimodal large language models using reinforcement learning from human feedback?you: not recommendedAI recommended (in order):
- Hugging Face Transformers (huggingface/transformers)
- PEFT (huggingface/peft)
- TRL (huggingface/trl)
- Alignment Handbook (huggingface/alignment-handbook)
- DeepSpeed (microsoft/DeepSpeed)
- RLlib (ray-project/ray)
- Ray (ray-project/ray)
- OpenAI Baselines (openai/baselines)
- Spinning Up (openai/spinningup)
- PyTorch Lightning (Lightning-AI/lightning)
- Keras (keras-team/keras)
AI recommended 11 alternatives but never named EvolvingLMMs-Lab/open-r1-multimodal. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking tools for fine-tuning vision-language models with reinforcement learning for math tasks.you: not recommendedAI recommended (in order):
- Hugging Face Transformers (huggingface/transformers)
- TRL (huggingface/trl)
- 🤗 Accelerate (huggingface/accelerate)
- 🤗 Datasets (huggingface/datasets)
- PyTorch (pytorch/pytorch)
- Stable Baselines3 (DLR-RM/stable-baselines3)
- Acme (deepmind/acme)
- TensorFlow (tensorflow/tensorflow)
- TF-Agents (tensorflow/agents)
- RLlib (ray-project/ray)
AI recommended 10 alternatives but never named EvolvingLMMs-Lab/open-r1-multimodal. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- 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 EvolvingLMMs-Lab/open-r1-multimodal?passAI did not name EvolvingLMMs-Lab/open-r1-multimodal — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts EvolvingLMMs-Lab/open-r1-multimodal in production, what risks or prerequisites should they evaluate first?passAI named EvolvingLMMs-Lab/open-r1-multimodal 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 EvolvingLMMs-Lab/open-r1-multimodal solve, and who is the primary audience?passAI did not name EvolvingLMMs-Lab/open-r1-multimodal — likely talking about a different project
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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EvolvingLMMs-Lab/open-r1-multimodal — 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