✨RynnVLA-002: A Unified Vision-Language-Action and World Model

📝 Summary:
RynnVLA-002 unifies a Vision-Language-Action and world model, enabling joint learning of environmental dynamics and action planning. This mutual enhancement leads to superior performance, achieving 97.4% success in simulation and a 50% boost in real-world robot tasks.

🔹 Publication Date: Published on Nov 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.17502
• PDF: https://arxiv.org/pdf/2511.17502
• Github: https://github.com/alibaba-damo-academy/RynnVLA-002

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For more data science resources:
✓ https://t.iss.one/DataScienceT

#VisionLanguageAction #WorldModels #Robotics #AI #DeepLearning

✨EvoVLA: Self-Evolving Vision-Language-Action Model

📝 Summary:
EvoVLA is a self-supervised VLA framework tackling stage hallucination in long-horizon robotic manipulation. It uses triplet contrastive learning, pose-based exploration, and memory to prevent shortcuts. EvoVLA significantly improves success, sample efficiency, and reduces hallucination in sim an...

🔹 Publication Date: Published on Nov 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.16166
• PDF: https://arxiv.org/pdf/2511.16166
• Project Page: https://aigeeksgroup.github.io/EvoVLA/
• Github: https://aigeeksgroup.github.io/EvoVLA/

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For more data science resources:
✓ https://t.iss.one/DataScienceT

#Robotics #VisionLanguageAction #SelfSupervisedLearning #AI #DeepLearning