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Shanghai Jiao Tong University
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TANGO enables humanoid robots to navigate cluttered spaces with unprecedented language-guided precision, achieving state-of-the-art performance without real-world training.
The latest AI City Challenge reveals that integrating foundation models with synthetic data design can significantly boost performance in complex urban scenarios.
OrganLens achieves unprecedented organ-specific representation learning in CT scans, significantly boosting diagnostic accuracy without requiring external segmentation.
UniNote's two-stage training, combining contrastive SFT and RL, leapfrogs existing multimodal embeddings, delivering SOTA item-to-item retrieval performance with improved cost efficiency in real-world deployments.
