Search papers, labs, and topics across Lattice.
4
0
7
Grounding item representations in user behavior can dramatically elevate the accuracy of sequential recommendations, bridging the gap between semantic understanding and real-world interactions.
Treating raw visual images as action representations revolutionizes embodied world models, leading to unprecedented generalization and control capabilities.
By allowing non-keyframes to skip denoising steps, RhymeFlow achieves faster video generation without compromising on visual quality.
$\tau_0$-WM outperforms traditional models by seamlessly integrating action prediction and evaluation, leading to superior performance in complex robotic tasks.
