To push forward general robotic grasping, we introduce a large-scale reasoning-based affordance segmentation benchmark, RAGNet. It contains 273k images, 180 categories, and 26k reasoning instructions.
Abstract: An Enhanced version of the RAG framework is proposed to improve the Groundedness of Medical Question Answering systems. It achieves higher retrieval effectiveness and response generation due ...
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