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Collections including paper arxiv:2504.10483

Is Noise Conditioning Necessary for Denoising Generative Models?

Paper • 2502.13129 • Published Feb 18 • 1
REPA-E: Unlocking VAE for End-to-End Tuning with Latent Diffusion Transformers

Paper • 2504.10483 • Published Apr 14 • 21
Mean Flows for One-step Generative Modeling

Paper • 2505.13447 • Published May 19 • 7
Latent Diffusion Model without Variational Autoencoder

Paper • 2510.15301 • Published Oct 17 • 48

Boosting Generative Image Modeling via Joint Image-Feature Synthesis

Paper • 2504.16064 • Published Apr 22 • 14
LoftUp: Learning a Coordinate-Based Feature Upsampler for Vision Foundation Models

Paper • 2504.14032 • Published Apr 18 • 7
Towards Understanding Camera Motions in Any Video

Paper • 2504.15376 • Published Apr 21 • 157
Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning

Paper • 2504.17192 • Published Apr 24 • 120

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Paper • 2503.07536 • Published Mar 10 • 88
Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model

Paper • 2503.07703 • Published Mar 10 • 37
Gemini Embedding: Generalizable Embeddings from Gemini

Paper • 2503.07891 • Published Mar 10 • 45
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

Paper • 2503.07572 • Published Mar 10 • 47

M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding

Paper • 2411.04952 • Published Nov 7, 2024 • 30
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models

Paper • 2411.05005 • Published Nov 7, 2024 • 13
M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models

Paper • 2411.04075 • Published Nov 6, 2024 • 17
Self-Consistency Preference Optimization

Paper • 2411.04109 • Published Nov 6, 2024 • 19

Test-Time Scaling with Reflective Generative Model

Paper • 2507.01951 • Published Jul 2 • 107
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Paper • 2502.05171 • Published Feb 7 • 151
Autoregressive Diffusion Models

Paper • 2110.02037 • Published Oct 5, 2021
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Paper • 2502.09509 • Published Feb 13 • 8

An Empirical Study of GPT-4o Image Generation Capabilities

Paper • 2504.05979 • Published Apr 8 • 64
Antidistillation Sampling

Paper • 2504.13146 • Published Apr 17 • 59
Generate, but Verify: Reducing Hallucination in Vision-Language Models with Retrospective Resampling

Paper • 2504.13169 • Published Apr 17 • 39
WORLDMEM: Long-term Consistent World Simulation with Memory

Paper • 2504.12369 • Published Apr 16 • 35

Image Generation

Image Generation

Causal Diffusion Transformers for Generative Modeling

Paper • 2412.12095 • Published Dec 16, 2024 • 23
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training

Paper • 2412.09619 • Published Dec 12, 2024 • 28
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation

Paper • 2412.07589 • Published Dec 10, 2024 • 48
Flowing from Words to Pixels: A Framework for Cross-Modality Evolution

Paper • 2412.15213 • Published Dec 19, 2024 • 28

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

Paper • 2401.09048 • Published Jan 17, 2024 • 10
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18, 2024 • 18
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Paper • 2401.10891 • Published Jan 19, 2024 • 62
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild

Paper • 2401.13627 • Published Jan 24, 2024 • 77

Is Noise Conditioning Necessary for Denoising Generative Models?

Paper • 2502.13129 • Published Feb 18 • 1
REPA-E: Unlocking VAE for End-to-End Tuning with Latent Diffusion Transformers

Paper • 2504.10483 • Published Apr 14 • 21
Mean Flows for One-step Generative Modeling

Paper • 2505.13447 • Published May 19 • 7
Latent Diffusion Model without Variational Autoencoder

Paper • 2510.15301 • Published Oct 17 • 48

Test-Time Scaling with Reflective Generative Model

Paper • 2507.01951 • Published Jul 2 • 107
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Paper • 2502.05171 • Published Feb 7 • 151
Autoregressive Diffusion Models

Paper • 2110.02037 • Published Oct 5, 2021
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Paper • 2502.09509 • Published Feb 13 • 8

Boosting Generative Image Modeling via Joint Image-Feature Synthesis

Paper • 2504.16064 • Published Apr 22 • 14
LoftUp: Learning a Coordinate-Based Feature Upsampler for Vision Foundation Models

Paper • 2504.14032 • Published Apr 18 • 7
Towards Understanding Camera Motions in Any Video

Paper • 2504.15376 • Published Apr 21 • 157
Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning

Paper • 2504.17192 • Published Apr 24 • 120

An Empirical Study of GPT-4o Image Generation Capabilities

Paper • 2504.05979 • Published Apr 8 • 64
Antidistillation Sampling

Paper • 2504.13146 • Published Apr 17 • 59
Generate, but Verify: Reducing Hallucination in Vision-Language Models with Retrospective Resampling

Paper • 2504.13169 • Published Apr 17 • 39
WORLDMEM: Long-term Consistent World Simulation with Memory

Paper • 2504.12369 • Published Apr 16 • 35

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Paper • 2503.07536 • Published Mar 10 • 88
Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model

Paper • 2503.07703 • Published Mar 10 • 37
Gemini Embedding: Generalizable Embeddings from Gemini

Paper • 2503.07891 • Published Mar 10 • 45
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

Paper • 2503.07572 • Published Mar 10 • 47

Image Generation

Image Generation

Causal Diffusion Transformers for Generative Modeling

Paper • 2412.12095 • Published Dec 16, 2024 • 23
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training

Paper • 2412.09619 • Published Dec 12, 2024 • 28
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation

Paper • 2412.07589 • Published Dec 10, 2024 • 48
Flowing from Words to Pixels: A Framework for Cross-Modality Evolution

Paper • 2412.15213 • Published Dec 19, 2024 • 28

M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding

Paper • 2411.04952 • Published Nov 7, 2024 • 30
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models

Paper • 2411.05005 • Published Nov 7, 2024 • 13
M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models

Paper • 2411.04075 • Published Nov 6, 2024 • 17
Self-Consistency Preference Optimization

Paper • 2411.04109 • Published Nov 6, 2024 • 19

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

Paper • 2401.09048 • Published Jan 17, 2024 • 10
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18, 2024 • 18
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Paper • 2401.10891 • Published Jan 19, 2024 • 62
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild

Paper • 2401.13627 • Published Jan 24, 2024 • 77

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