Hugging Face Trending Papers
VISTA: Test-Time Compositional Alignment for Visual Autoregressive Generation
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arXiv Computer Vision
Aug 25
VISTA: Test-Time Compositional Alignment for Visual Autoregressive Generation
VISTA is a gradient‑based test‑time alignment framework designed for next‑scale visual autoregressive (VAR) image generation. It optimizes intermediate representations within the frozen transformer to enforce compositional constraints, without altering model weights or requiring extra training. Experiments on two benchmarks and two model scales show that VISTA improves compositional accuracy by up to 20% on a 2B backbone and 6% on an 8B backbone, while preserving image quality and enabling a smaller model to outperform a larger one.
arXiv Computer Vision
3d ago
NoisEasier: Test-Time Noise Optimization for Text-to-Video Generation
arXiv:2608.30194v1 Announce Type: new Abstract: Diffusion models have recently advanced text-to-video (T2V) generation, yet they still struggle with fine-grained compositional alignment, such as attr...
arXiv Computer Vision
2d ago
DiverseVAR: Balancing Diversity and Quality of Next-Scale Visual Autoregressive Models
arXiv:2511.21415v2 Announce Type: replace Abstract: We introduce DiverseVAR, a framework that enhances the diversity of text-conditioned visual autoregressive models (VAR) at test time without requir...
arXiv AI
Jun 2
Improving Visual Representation Alignment Generation with GRPO
arXiv:2606. 00583v1 Announce Type: cross Abstract: Recent diffusion transformers have demonstrated strong image synthesis capabilities but remain inefficient to train due to weak alignment between generative and discriminative representations.
Hugging Face Trending Papers
Jul 27
UniGen-AR: Unifying Visual Generation with Auto-Regressive Modeling
Modern computer vision pipelines remain fragmented, with tasks such as text-to-image generation, editing, restoration, and classical perception handled by separate models. We study Unified Visual Generation (UVG), where a single model produces diverse image-valued outputs through a unified multimodal interface.
arXiv AI
Jul 13
Video Generation Models are General-Purpose Vision Learners
arXiv:2607. 09024v1 Announce Type: cross Abstract: Driven by next-token prediction, NLP shifted from task-specific models into powerful generalist foundation models.