5 citations · 7 across the 10 of their papers we have counts for
5 papers · 1 filter
Iterative Refinement Improves Compositional Image Generation
Shantanu Jaiswal, Mihir Prabhudesai, Nikash Bhardwaj +5
Text-to-image (T2I) models have achieved remarkable progress, yet they continue to struggle with complex prompts that require simultaneously handling multiple objects, relations, a…
Unified Multimodal Discrete Diffusion
Alexander Swerdlow, Mihir Prabhudesai, Siddharth Gandhi +2
Multimodal generative models that can understand and generate across multiple modalities are dominated by autoregressive (AR) approaches, which process tokens sequentially from lef…
Video Diffusion Alignment via Reward Gradients
Mihir Prabhudesai, Russell Mendonca, Zheyang Qin +2
We have made significant progress towards building foundational video diffusion models. As these models are trained using large-scale unsupervised data, it has become crucial to ad…
Diffusion-TTA: Test-time Adaptation of Discriminative Models via Generative Feedback
Mihir Prabhudesai, Tsung-Wei Ke, Alexander C. Li +2
The advancements in generative modeling, particularly the advent of diffusion models, have sparked a fundamental question: how can these models be effectively used for discriminati…
Aligning Text-to-Image Diffusion Models with Reward Backpropagation
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak +1
Text-to-image diffusion models have recently emerged at the forefront of image generation, powered by very large-scale unsupervised or weakly supervised text-to-image training data…