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Motion transfer can now succeed across vastly different object categories, achieving state-of-the-art fidelity without relying on fixed structural correspondences.
LGRID transforms the landscape of local-life service recommendations by generating interpretable Semantic IDs that are both semantically rich and collision-resistant.
SVD-Attention slashes the quadratic cost of attention to linear for recommendation tasks by exploiting the inherent low-rank structure of user behavior sequences, without sacrificing softmax.
FlashEvaluator slashes the computational cost of evaluating multiple sequences in Generator-Evaluator frameworks while boosting accuracy by enabling direct cross-sequence comparisons.
Achieve lifelike character animation with 10x faster inference using Kling-MotionControl, a DiT-based framework that intelligently handles body, face, and hand motions.
Forget separate image and video models: VINO's single diffusion backbone handles both, opening the door to truly unified visual creation and editing.
