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By dynamically updating retrieval memory based on past successes, GAM-RAG slashes inference costs by 61% while boosting RAG performance by nearly 4%.
By unifying hand motion estimation and generation into a single diffusion framework, UniHand handles heterogeneous inputs and challenging conditions like occlusions better than task-specific models.
