Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
Paper
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2412.10208
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Published
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19
Generative Modeling Approachs
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Normalizing Flows are Capable Generative Models
Paper • 2412.06329 • Published • 11 -
A Noise is Worth Diffusion Guidance
Paper • 2412.03895 • Published • 29 -
Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models
Paper • 2501.01423 • Published • 44 -
Diffusion Models without Classifier-free Guidance
Paper • 2502.12154 • Published • 8 -
Studying Classifier(-Free) Guidance From a Classifier-Centric Perspective
Paper • 2503.10638 • Published • 2 -
FlowTok: Flowing Seamlessly Across Text and Image Tokens
Paper • 2503.10772 • Published • 19 -
Gaussian Mixture Flow Matching Models
Paper • 2504.05304 • Published • 11 -
Continuous Visual Autoregressive Generation via Score Maximization
Paper • 2505.07812 • Published • 12 -
Unified Continuous Generative Models
Paper • 2505.07447 • Published • 43 -
Accelerate TarFlow Sampling with GS-Jacobi Iteration
Paper • 2505.12849 • Published • 7 -
Discrete Markov Bridge
Paper • 2505.19752 • Published • 17 -
Transition Models: Rethinking the Generative Learning Objective
Paper • 2509.04394 • Published • 28 -
Diffusion Transformers with Representation Autoencoders
Paper • 2510.11690 • Published • 165 -
Latent Diffusion Model without Variational Autoencoder
Paper • 2510.15301 • Published • 49