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Robot policies learn 4x faster by co-evolving their training environments with a critic that diagnoses and recreates failure modes.
Topology-preserving 3D generation now achieves 98% fewer tokens and 58.5% faster inference by encoding shapes as overlapping slice latents instead of expensive voxels.
Achieving 74.8% accuracy on a new temporal reasoning benchmark, ChronoVision redefines how multimodal models can tackle complex visual tasks.
Current models struggle with the complexities of children's gait, revealing a critical gap in automated assessment tools for pediatric neuromuscular disorders.
ELSA3D outperforms existing unified 3D models by halving computational costs while enhancing cross-modal reasoning precision.
Text-to-3D generation gets a semantic upgrade: DreamPartGen creates 3D objects with parts that not only look right but also understand their relationships and align with textual descriptions.