{"total":69,"rows":[{"id":"2505.13211","title":"MAGI-1: Autoregressive Video Generation at Scale","created":"2025-05-19","cited_by_count":276,"area":"wm"},{"id":"2501.09685","title":"Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review","created":"2025-01-16","cited_by_count":88,"area":"diffusion"},{"id":"2401.08092","title":"A Survey of Resource-efficient LLM and Multimodal Foundation Models","created":"2024-01-16","cited_by_count":86,"area":null},{"id":"2405.18407","title":"Phased Consistency Models","created":"2024-05-28","cited_by_count":85,"area":"diffusion"},{"id":"2403.18103","title":"Tutorial on Diffusion Models for Imaging and Vision","created":"2024-03-26","cited_by_count":49,"area":"diffusion"},{"id":"2412.08635","title":"Multimodal Latent Language Modeling with Next-Token Diffusion","created":"2024-12-11","cited_by_count":48,"area":"mllm"},{"id":"2408.14340","title":"Foundation Models for Music: A Survey","created":"2024-08-26","cited_by_count":37,"area":"diffusion"},{"id":"2501.00375","title":"Token Pruning for Caching Better: 9 Times Acceleration on Stable Diffusion for Free","created":"2024-12-31","cited_by_count":30,"area":"diffusion"},{"id":"2606.05254","title":"Flash-WAM: Modality-Aware Distillation for World Action Models","created":"2026-06-03","cited_by_count":19,"area":"wm"},{"id":"2408.07476","title":"One Step Diffusion-based Super-Resolution with Time-Aware Distillation","created":"2024-08-14","cited_by_count":17,"area":"diffusion"},{"id":"2503.05156","title":"Accelerating Diffusion Transformer via Gradient-Optimized Cache","created":"2025-03-07","cited_by_count":15,"area":"diffusion"},{"id":"2608.13546","title":"Alaya-EVOKE: From Linear-Scaling Supervision to Endless World","created":"2026-08-13","cited_by_count":14,"area":"wm"},{"id":"2508.04016","title":"S$^2$Q-VDiT: Accurate Quantized Video Diffusion Transformer with Salient Data and Sparse Token Distillation","created":"2025-08-06","cited_by_count":13,"area":"diffusion"},{"id":"2503.07154","title":"Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms","created":"2025-03-10","cited_by_count":12,"area":"lr"},{"id":"2412.05899","title":"Accelerating Video Diffusion Models via Distribution Matching","created":"2024-12-08","cited_by_count":11,"area":"diffusion"},{"id":"2410.18958","title":"Stable Consistency Tuning: Understanding and Improving Consistency Models","created":"2024-10-24","cited_by_count":9,"area":"diffusion"},{"id":"2411.16164","title":"Text-to-Image Synthesis: A Decade Survey","created":"2024-11-25","cited_by_count":9,"area":null},{"id":"2510.01068","title":"Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition","created":"2025-10-01","cited_by_count":9,"area":"vla"},{"id":"2412.20378","title":"Tri-Ergon: Fine-grained Video-to-Audio Generation with Multi-modal Conditions and LUFS Control","created":"2024-12-29","cited_by_count":8,"area":null},{"id":"2604.23380","title":"V-GRPO: Online Reinforcement Learning for Denoising Generative Models Is Easier than You Think","created":"2026-04-25","cited_by_count":7,"area":"lr"},{"id":"2412.06578","title":"MoViE: Mobile Diffusion for Video Editing","created":"2024-12-09","cited_by_count":6,"area":"diffusion"},{"id":"2511.19917","title":"Scale Where It Matters: Training-Free Localized Scaling for Diffusion Models","created":"2025-11-25","cited_by_count":6,"area":"lr"},{"id":"2503.15457","title":"Di$\\mathtt{[M]}$O: Distilling Masked Diffusion Models into One-step Generator","created":"2025-03-19","cited_by_count":5,"area":"diffusion"},{"id":"2609.05588","title":"GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation","created":"2026-09-04","cited_by_count":5,"area":"wm"},{"id":"2302.12255","title":"Modeling Molecular Structures with Intrinsic Diffusion Models","created":"2023-02-23","cited_by_count":4,"area":"diffusion"},{"id":"2306.13720","title":"Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image Attenuation","created":"2023-06-23","cited_by_count":4,"area":"diffusion"},{"id":"2509.10122","title":"Realism Control One-step Diffusion for Real-World Image Super-Resolution","created":"2025-09-12","cited_by_count":4,"area":"diffusion"},{"id":"2604.04018","title":"1.x-Distill: Breaking the Diversity, Quality, and Efficiency Barrier in Distribution Matching Distillation","created":"2026-04-05","cited_by_count":4,"area":"diffusion"},{"id":"2402.02977","title":"Variational Flow Models: Flowing in Your Style","created":"2024-02-05","cited_by_count":3,"area":"diffusion"},{"id":"2412.09656","title":"From Noise to Nuance: Advances in Deep Generative Image Models","created":"2024-12-12","cited_by_count":3,"area":"diffusion"},{"id":"2501.00941","title":"A Novel Diffusion Model for Pairwise Geoscience Data Generation with Unbalanced Training Dataset","created":"2025-01-01","cited_by_count":3,"area":"diffusion"},{"id":"2511.08930","title":"From Structure to Detail: Hierarchical Distillation for Efficient Diffusion Model","created":"2025-11-12","cited_by_count":3,"area":"diffusion"},{"id":"2607.19064","title":"Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing","created":"2026-07-21","cited_by_count":3,"area":"diffusion"},{"id":"2408.03433","title":"Hybrid diffusion models: combining supervised and generative pretraining for label-efficient fine-tuning of segmentation models","created":"2024-08-06","cited_by_count":2,"area":"diffusion"},{"id":"2412.19489","title":"RAIN: Real-time Animation of Infinite Video Stream","created":"2024-12-27","cited_by_count":2,"area":"diffusion"},{"id":"2503.07120","title":"FEB-Cache: Frequency-Guided Exposure Bias Reduction for Enhancing Diffusion Transformer Caching","created":"2025-03-10","cited_by_count":2,"area":"diffusion"},{"id":"2512.05092","title":"Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction","created":"2025-12-04","cited_by_count":2,"area":"diffusion"},{"id":"2605.21489","title":"Variance Reduction for Expectations with Diffusion Teachers","created":"2026-05-20","cited_by_count":2,"area":"diffusion"},{"id":"2401.06127","title":"E$^{2}$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation","created":"2024-01-11","cited_by_count":1,"area":"diffusion"},{"id":"2504.06803","title":"DyDiT++: Diffusion Transformers with Timestep and Spatial Dynamics for Efficient Visual Generation","created":"2025-04-09","cited_by_count":1,"area":"diffusion"},{"id":"2511.08823","title":"DT-NVS: Diffusion Transformers for Novel View Synthesis","created":"2025-11-11","cited_by_count":1,"area":"diffusion"},{"id":"2512.08985","title":"Verifier Threshold: An Efficient Test-Time Scaling Approach for Image Generation","created":"2025-12-06","cited_by_count":1,"area":"lr"},{"id":"2607.26723","title":"FARI: Robust One-Step Inversion for Watermarking in Diffusion Models","created":"2026-07-29","cited_by_count":1,"area":"diffusion"},{"id":"2608.07620","title":"FlowErase-OPD: Multi-Concept Erasure via Anchored On-Policy Distillation in Flow Matching Models","created":"2026-08-07","cited_by_count":1,"area":"diffusion"},{"id":"2411.10863","title":"Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model","created":"2024-11-16","cited_by_count":0,"area":"diffusion"},{"id":"2411.17535","title":"IMPROVE: Improving Medical Plausibility without Reliance on HumanValidation -- An Enhanced Prototype-Guided Diffusion Framework","created":"2024-11-26","cited_by_count":0,"area":"diffusion"},{"id":"2412.05780","title":"BudgetFusion: Perceptually-Guided Adaptive Diffusion Models","created":"2024-12-08","cited_by_count":0,"area":"diffusion"},{"id":"2412.17162","title":"Generative Diffusion Modeling: A Practical Handbook","created":"2024-12-22","cited_by_count":0,"area":"diffusion"},{"id":"2412.21044","title":"E2ED^2:Direct Mapping from Noise to Data for Enhanced Diffusion Models","created":"2024-12-30","cited_by_count":0,"area":"diffusion"},{"id":"2501.18736","title":"Distillation-Driven Diffusion Model for Multi-Scale MRI Super-Resolution: Make 1.5T MRI Great Again","created":"2025-01-30","cited_by_count":0,"area":"diffusion"},{"id":"2502.14226","title":"Designing Parameter and Compute Efficient Diffusion Transformers using Distillation","created":"2025-02-20","cited_by_count":0,"area":"diffusion"},{"id":"2512.04499","title":"Back to Basics: Motion Representation Matters for Human Motion Generation Using Diffusion Model","created":"2025-12-04","cited_by_count":0,"area":"diffusion"},{"id":"2603.25872","title":"DRiffusion: Draft-and-Refine Process Parallelizes Diffusion Models with Ease","created":"2026-03-26","cited_by_count":0,"area":"diffusion"},{"id":"2606.08751","title":"Less Is More: Training-Free Acceleration Framework of 3D Diffusion Models for Low-Count PET Denoising via Global-Local Trajectory Reduction","created":"2026-06-07","cited_by_count":0,"area":"diffusion"},{"id":"2606.12072","title":"World Model Self-Distillation: Training World Models to Solve General Tasks","created":"2026-06-10","cited_by_count":0,"area":"wm"},{"id":"2607.04112","title":"DynaVieW: Schema-Guided World Modeling for Understanding Hierarchical Visual Dynamics","created":"2026-07-05","cited_by_count":0,"area":"wm"},{"id":"2607.10329","title":"Imperceptible and Reversible Adversarial Examples against Vision-Language Models for Privacy Protection","created":"2026-07-11","cited_by_count":0,"area":"mllm"},{"id":"2607.17560","title":"Reinforcement Learning: From Algorithms To Foundation Models","created":"2026-07-20","cited_by_count":0,"area":"wm"},{"id":"2607.27431","title":"SE(3)-MeanFlow: Few-Step Protein Backbone Generation on Lie Groups","created":"2026-07-29","cited_by_count":0,"area":"diffusion"},{"id":"2608.16354","title":"DriveCache: Action-Aware Caching for Driving World Model Inference","created":"2026-08-17","cited_by_count":0,"area":"wm"},{"id":"2609.04778","title":"Diffusion Language Models for Mobile Edge Agentic AI: Foundations, Applications, and Challenges","created":"2026-09-04","cited_by_count":0,"area":"diffusion"},{"id":"2610.06509","title":"Xaurora: Generative Weather Forecasting with Denoising Stochastic Interpolants from a Foundation Model Prior","created":"2026-10-05","cited_by_count":0,"area":null},{"id":"2610.06520","title":"Conditional Flow Matching for Single-Neuron Electrophysiology: Capturing Multimodal Responses Across Stimuli","created":"2026-10-05","cited_by_count":0,"area":"diffusion"},{"id":"2610.06617","title":"RealtimeWAM: One-Step Asynchronous World Action Models","created":"2026-10-05","cited_by_count":0,"area":"wm"},{"id":"2610.09221","title":"Consistent Distribution Matching for Data-Free Diffusion Distillation","created":"2026-10-06","cited_by_count":0,"area":"diffusion"},{"id":"2610.10990","title":"Omni-Diffusion-Distill: Few-Step Distillation of Unified Multimodal Diffusion Large Language Models","created":"2026-10-07","cited_by_count":0,"area":null},{"id":"2610.11362","title":"Bernoulli Flow Models: Self-Consistent Generative Modeling for Binary Data","created":"2026-10-08","cited_by_count":0,"area":"diffusion"},{"id":"2610.11376","title":"CRISP: Fixing Flying Pixels in Latent LiDAR Generation via Diffusion Decoding","created":"2026-10-08","cited_by_count":0,"area":null},{"id":"2610.12156","title":"Connected Self Forcing: Beyond Local Learning in Video Autoregression","created":"2026-10-08","cited_by_count":0,"area":null}],"next_cursor":null}