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VGGD achieves superior rendering quality and geometric consistency by integrating pretrained visual geometry priors into the reconstruction process.
VLM-hyster achieves unprecedented segmentation accuracy in hysteroscopic surgeries, outperforming all existing models and paving the way for more effective AI-assisted surgical interventions.
Injecting 4D geometric priors into World Action Models boosts robotic manipulation performance without adding inference overhead.
PiL-World slashes the gap between simulated and real-world VLA success rates by over 50%, revolutionizing how we evaluate robotic policies.
Training video object segmentation models with just text expressions could revolutionize the field by drastically reducing the need for expensive annotations.
Force GNNs to explicitly reason about graph-level concepts and you get state-of-the-art performance in both classification and interpretability.
