NVlabs/Long-RL

• highreadme#1

  Add a concise, high-level summary to the README's opening

  原因：

  当前

  # Long-RL: Scaling RL to Long Sequences
  
  [](https://arxiv.org/abs/2507.07966)
  [](https://github.com/NVlabs/Long-RL)
  [](https://huggingface.co/Efficient-Large-Model/LongVILA-R1-7B)
  [](https://www.youtube.com/watch?v=ykbblK2jiEg)
  [](https://long-rl.hanlab.ai)
  
  <div align="center">
  
  [](https://www.youtube.com/watch?v=ykbblK2jiEg)
  
  </div>
  
  **Scaling RL to Long Videos [Paper]** <br />
  Yukang Chen *, Wei Huang *, Baifeng Shi, Qinghao Hu, Hanrong Ye, Ligeng Zhu, Zhijian Liu, Pavlo Molchanov, Jan Kautz, Xiaojuan Qi, Sifei Liu,Hongxu Yin, Yao Lu, Song Han <br />
  
  We introduce a full-stack framework that scales up reasoning in vision-language models (VLMs) to long videos, leveraging reinforcement learning.

  复制粘贴的修复

  复制

  # Long-RL: Scaling RL to Long Sequences
  
  This repository introduces a full-stack framework for scaling reinforcement learning to enable reasoning in vision-language models (VLMs) over very long video sequences.
  
  [](https://arxiv.org/abs/2507.07966)
  [](https://github.com/NVlabs/Long-RL)
  [](https://huggingface.co/Efficient-Large-Model/LongVILA-R1-7B)
  [](https://www.youtube.com/watch?v=ykbblK2jiEg)
  [](https://long-rl.hanlab.ai)
  
  <div align="center">
  
  [](https://www.youtube.com/watch?v=ykbblK2jiEg)
  
  </div>
  
  **Scaling RL to Long Videos [Paper]** <br />
  Yukang Chen *, Wei Huang *, Baifeng Shi, Qinghao Hu, Hanrong Ye, Ligeng Zhu, Zhijian Liu, Pavlo Molchanov, Jan Kautz, Xiaojuan Qi, Sifei Liu,Hongxu Yin, Yao Lu, Song Han <br />
  
  We introduce a full-stack framework that scales up reasoning in vision-language models (VLMs) to long videos, leveraging reinforcement learning.

  待办完成忽略
• mediumabout#2

  Add the project homepage URL to the About section

  原因：

  复制粘贴的修复

  复制

  https://long-rl.hanlab.ai

  待办完成忽略
• mediumtopics#3

  Add more specific topics for video reasoning and VLMs

  原因：

  当前

  efficient-ai, large-language-models, long-sequence, multi-modality, reinforcement-learning, sequence-parallelism

  复制粘贴的修复

  复制

  video-reasoning, vision-language-models, long-video-rl

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How to apply reinforcement learning effectively for reasoning over very long video sequences?

  你：未被推荐
  AI 推荐顺序：

  1. Acme (deepmind/acme)
  2. Perceiver IO
  3. VideoMAE (facebookresearch/VideoMAE)
  4. RLlib
  5. Ray (ray-project/ray)
  6. Stable Baselines3 (DLR-RM/stable-baselines3)
  7. TimeSformer (facebookresearch/TimeSformer)
  8. MViT (facebookresearch/mvit)
  9. TorchRL (pytorch/rl)
  10. Dopamine (google/dopamine)
  11. Gymnasium (Farama-Foundation/Gymnasium)
  12. OpenAI Gym (openai/gym)
  13. PyTorchVideo (facebookresearch/pytorchvideo)

  AI 推荐了 13 个替代方案，却始终没点名 NVlabs/Long-RL。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Seeking frameworks to combine large vision-language models with RL for long-sequence multi-modal tasks.

  你：未被推荐
  AI 推荐顺序：

  1. Hugging Face Transformers
  2. TRL (Transformer Reinforcement Learning)
  3. Stable Baselines3
  4. RLlib
  5. Acme
  6. Gymnasium
  7. PyTorch
  8. TensorFlow
  9. Minerva
  10. DreamerV3
  11. PlaNet
  12. RoboStack
  13. ROS (Robot Operating System)
  14. MoveIt

  AI 推荐了 14 个替代方案，却始终没点名 NVlabs/Long-RL。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of NVlabs/Long-RL?

  pass
  ✓AI 明确点名了 NVlabs/Long-RL

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts NVlabs/Long-RL in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 NVlabs/Long-RL

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo NVlabs/Long-RL solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 NVlabs/Long-RL

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？