Search papers, labs, and topics across Lattice.
3
0
4
4
GraphVid achieves superior video quality and controllability with significantly less training data, revolutionizing how we can interact with multi-object video generation.
Forget GAN inversions – now you can steer diffusion models with a dynamically weighted soup of differentiable rewards, including a VQA-based reward for language-vision reasoning, and get SOTA image edits.
Achieve SOTA multimodal performance across eight benchmarks and strong zero-shot generalization without task-specific training by decoupling understanding and generation via unified discrete flow matching.
