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GASE reduces the sim-to-real performance gap to under 10% while outperforming existing methods in segmentation accuracy by over 10%.
Bridging the gap in multi-camera depth prediction, SurroundNEXO achieves a 33.2% reduction in single-view error by rethinking how we leverage ego-centric geometry.
YouZhi-LLM achieves unprecedented concurrency and accuracy in financial LLMs by dramatically reducing KV-cache overhead, setting a new standard for deployment efficiency.
Breaking the symmetry in adversarial distillation allows AAD-1 to generate videos that maintain dynamic motion without collapsing into static sequences.
Forget hand-crafted benchmarks: CUA-Gym's auto-generated training data lets computer-use agents crush existing open-source models on real-world tasks.
