1.2k citations · 2.2k across the 48 of their papers we have counts for
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FeaTok: Feature-Loss Tokenization for Image Generation
Zhang Xiaofeng, Samuel Lavoie, Nicolas Beltran-Velez +6
Discrete image generators learn the distribution of tokens produced by an image tokenizer. These token representations should be easy for generators to model, not merely enable fai…
Inference-time Physics Alignment of Video Generative Models with Latent World Models
Jianhao Yuan, Xiaofeng Zhang, Felix Friedrich +7
State-of-the-art video generative models produce promising visual content yet often violate basic physics principles, limiting their utility. While some attribute this deficiency t…
GASS: Geometry-Aware Spherical Sampling for Disentangled Diversity Enhancement in Text-to-Image Generation
Ye Zhu, Kaleb S. Newman, Johannes F. Lutzeyer +3
Despite high semantic alignment, modern text-to-image (T2I) generative models still struggle to synthesize diverse images from a given prompt. In this work, we enhance the T2I dive…
Unified Text-Image Generation with Weakness-Targeted Post-Training
Jiahui Chen, Philippe Hansen-Estruch, Xiaochuang Han +7
Unified multimodal generation architectures that jointly produce text and images have recently emerged as a promising direction for text-to-image (T2I) synthesis. However, many exi…