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By explicitly filtering out visual clutter, HSC-VLA achieves a 52.4% performance boost in complex bimanual manipulation tasks compared to monolithic approaches.
Mamba's global context modeling gives YOLO a boost in murky underwater object detection, improving mAP by 4.9% over YOLOv8n.
Ditch the resampling: ReIMTS forecasts irregular time series 27% better by recursively splitting data and preserving original timestamps, unlocking crucial sampling pattern information.
Ditch slow optimization and template retrieval: PAct generates articulated 3D objects from a single image in a feed-forward manner, preserving instance-level detail and articulation plausibility.
