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TennisVAR redefines sports video analysis by grounding tactical reasoning in stroke-level evidence, enabling deeper insights into match strategies.
GFR-SAM reveals that training-free segmentation can outperform traditional methods by effectively utilizing cross-image cues and contrastive filtering.
PAR3D reveals that integrating part-aware representations can dramatically enhance 3D scene understanding, outperforming traditional object-centric models.
Fragmented medical data hurts MLLM performance: this paper shows how a hierarchical medical knowledge graph can be used to engineer training data that substantially improves MLLM accuracy on complex clinical tasks.
VideoLLMs can slash 70% of their tokens and still achieve state-of-the-art performance, thanks to a hierarchical pruning strategy that mirrors video structure and LLM information flow.