{"total":195,"rows":[{"id":"2312.00858","title":"DeepCache: Accelerating Diffusion Models for Free","created":"2023-12-01","cited_by_count":359,"area":"diffusion"},{"id":"2410.10733","title":"Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models","created":"2024-10-14","cited_by_count":217,"area":"diffusion"},{"id":"2308.06767","title":"A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations","created":"2023-08-13","cited_by_count":202,"area":null},{"id":"2406.01125","title":"$\\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers","created":"2024-06-03","cited_by_count":175,"area":"diffusion"},{"id":"2410.05317","title":"Accelerating Diffusion Transformers with Token-wise Feature Caching","created":"2024-10-05","cited_by_count":156,"area":"diffusion"},{"id":"2406.01733","title":"Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching","created":"2024-06-03","cited_by_count":142,"area":"diffusion"},{"id":"2407.01425","title":"FORA: Fast-Forward Caching in Diffusion Transformer Acceleration","created":"2024-07-01","cited_by_count":137,"area":"diffusion"},{"id":"2503.06923","title":"From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers","created":"2025-03-10","cited_by_count":136,"area":"diffusion"},{"id":"2405.03520","title":"Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond","created":"2024-05-06","cited_by_count":111,"area":"wm"},{"id":"2308.09388","title":"Diffusion Models for Image Restoration and Enhancement: A Comprehensive Survey","created":"2023-08-18","cited_by_count":109,"area":"diffusion"},{"id":"2308.10916","title":"Diffusion Model as Representation Learner","created":"2023-08-21","cited_by_count":95,"area":"diffusion"},{"id":"2406.17343","title":"Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers","created":"2024-06-25","cited_by_count":94,"area":"diffusion"},{"id":"2407.14041","title":"Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization","created":"2024-07-19","cited_by_count":71,"area":"diffusion"},{"id":"2308.14480","title":"Priority-Centric Human Motion Generation in Discrete Latent Space","created":"2023-08-28","cited_by_count":67,"area":"diffusion"},{"id":"2404.07850","title":"MindBridge: A Cross-Subject Brain Decoding Framework","created":"2024-04-11","cited_by_count":66,"area":null},{"id":"2410.03456","title":"Dynamic Diffusion Transformer","created":"2024-10-04","cited_by_count":62,"area":"diffusion"},{"id":"2306.04542","title":"On the Design Fundamentals of Diffusion Models: A Survey","created":"2023-06-07","cited_by_count":60,"area":"diffusion"},{"id":"2405.19237","title":"ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning","created":"2024-05-29","cited_by_count":55,"area":"diffusion"},{"id":"2411.13383","title":"Adversarial Diffusion Compression for Real-World Image Super-Resolution","created":"2024-11-20","cited_by_count":52,"area":null},{"id":"2412.01199","title":"TinyFusion: Diffusion Transformers Learned Shallow","created":"2024-12-02","cited_by_count":45,"area":"diffusion"},{"id":"2410.16942","title":"DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization","created":"2024-10-22","cited_by_count":43,"area":"diffusion"},{"id":"2406.06890","title":"Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation","created":"2024-06-11","cited_by_count":39,"area":"diffusion"},{"id":"2405.05252","title":"Attention-Driven Training-Free Efficiency Enhancement of Diffusion Models","created":"2024-05-08","cited_by_count":38,"area":"diffusion"},{"id":"2406.02366","title":"Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models","created":"2024-06-04","cited_by_count":37,"area":"diffusion"},{"id":"2502.06805","title":"Efficient Diffusion Models: A Survey","created":"2025-02-03","cited_by_count":35,"area":"diffusion"},{"id":"2503.23367","title":"FastVAR: Linear Visual Autoregressive Modeling via Cached Token Pruning","created":"2025-03-30","cited_by_count":34,"area":"inference"},{"id":"2506.03065","title":"Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers","created":"2025-06-03","cited_by_count":34,"area":"diffusion"},{"id":"2402.14167","title":"T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching","created":"2024-02-21","cited_by_count":33,"area":"diffusion"},{"id":"2411.17787","title":"Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient","created":"2024-11-26","cited_by_count":33,"area":null},{"id":"2308.12216","title":"SG-Former: Self-guided Transformer with Evolving Token Reallocation","created":"2023-08-23","cited_by_count":32,"area":null},{"id":"2503.18414","title":"U-REPA: Aligning Diffusion U-Nets to ViTs","created":"2025-03-24","cited_by_count":32,"area":"diffusion"},{"id":"2407.12718","title":"SlimFlow: Training Smaller One-Step Diffusion Models with Rectified Flow","created":"2024-07-17","cited_by_count":30,"area":"diffusion"},{"id":"2412.10494","title":"SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device","created":"2024-12-13","cited_by_count":27,"area":"diffusion"},{"id":"2310.03337","title":"Denoising Diffusion Step-aware Models","created":"2023-10-05","cited_by_count":24,"area":"diffusion"},{"id":"2403.16627","title":"SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions","created":"2024-03-25","cited_by_count":24,"area":"diffusion"},{"id":"2503.15927","title":"BlockDance: Reuse Structurally Similar Spatio-Temporal Features to Accelerate Diffusion Transformers","created":"2025-03-20","cited_by_count":24,"area":"diffusion"},{"id":"2401.04585","title":"EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models","created":"2024-01-09","cited_by_count":23,"area":"diffusion"},{"id":"2406.06911","title":"AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising","created":"2024-06-11","cited_by_count":22,"area":"diffusion"},{"id":"2409.03550","title":"DKDM: Data-Free Knowledge Distillation for Diffusion Models with Any Architecture","created":"2024-09-05","cited_by_count":22,"area":"diffusion"},{"id":"2411.16720","title":"Importance-Based Token Merging for Efficient Image and Video Generation","created":"2024-11-23","cited_by_count":22,"area":"diffusion"},{"id":"2412.16822","title":"Layer- and Timestep-Adaptive Differentiable Token Compression Ratios for Efficient Diffusion Transformers","created":"2024-12-22","cited_by_count":22,"area":"diffusion"},{"id":"2312.03517","title":"FRDiff : Feature Reuse for Universal Training-free Acceleration of Diffusion Models","created":"2023-12-06","cited_by_count":20,"area":"diffusion"},{"id":"2312.05284","title":"SlimSAM: 0.1% Data Makes Segment Anything Slim","created":"2023-12-08","cited_by_count":20,"area":null},{"id":"2510.08669","title":"FreqCa: Accelerating Diffusion Models via Frequency-Aware Caching","created":"2025-10-09","cited_by_count":20,"area":"diffusion"},{"id":"2404.06091","title":"Hash3D: Training-free Acceleration for 3D Generation","created":"2024-04-09","cited_by_count":19,"area":"diffusion"},{"id":"2407.12173","title":"Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis","created":"2024-07-16","cited_by_count":19,"area":"diffusion"},{"id":"2510.06751","title":"OBS-Diff: Accurate Pruning For Diffusion Models in One-Shot","created":"2025-10-08","cited_by_count":19,"area":"diffusion"},{"id":"2404.10445","title":"SparseDM: Toward Sparse Efficient Diffusion Models","created":"2024-04-16","cited_by_count":18,"area":"diffusion"},{"id":"2406.05723","title":"Binarized Diffusion Model for Image Super-Resolution","created":"2024-06-09","cited_by_count":18,"area":"diffusion"},{"id":"2508.16212","title":"OmniCache: A Trajectory-Oriented Global Perspective on Training-Free Cache Reuse for Diffusion Transformer Models","created":"2025-08-22","cited_by_count":18,"area":"diffusion"},{"id":"2409.19128","title":"Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models","created":"2024-09-27","cited_by_count":17,"area":"diffusion"},{"id":"2505.11707","title":"Attend to Not Attended: Structure-then-Detail Token Merging for Post-training DiT Acceleration","created":"2025-05-16","cited_by_count":17,"area":"diffusion"},{"id":"2312.05431","title":"Efficient Quantization Strategies for Latent Diffusion Models","created":"2023-12-09","cited_by_count":16,"area":"diffusion"},{"id":"2510.19755","title":"A Survey on Cache Methods in Diffusion Models: Toward Efficient Multi-Modal Generation","created":"2025-10-22","cited_by_count":16,"area":"diffusion"},{"id":"2501.11587","title":"Recurrent Diffusion for Large-Scale Parameter Generation","created":"2025-01-20","cited_by_count":15,"area":null},{"id":"2309.17074","title":"AdaDiff: Accelerating Diffusion Models through Step-Wise Adaptive Computation","created":"2023-09-29","cited_by_count":14,"area":"diffusion"},{"id":"2401.09031","title":"Data Attribution for Diffusion Models: Timestep-induced Bias in Influence Estimation","created":"2024-01-17","cited_by_count":14,"area":"diffusion"},{"id":"2410.09873","title":"Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy","created":"2024-10-13","cited_by_count":14,"area":"diffusion"},{"id":"2411.01171","title":"Fast and Memory-Efficient Video Diffusion Using Streamlined Inference","created":"2024-11-02","cited_by_count":14,"area":"diffusion"},{"id":"2305.15798","title":"BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion","created":"2023-05-25","cited_by_count":13,"area":"diffusion"},{"id":"2406.12042","title":"Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models","created":"2024-06-17","cited_by_count":13,"area":"diffusion"},{"id":"2407.03917","title":"Timestep-Aware Correction for Quantized Diffusion Models","created":"2024-07-04","cited_by_count":13,"area":"diffusion"},{"id":"2407.21316","title":"Diff-Cleanse: Identifying and Mitigating Backdoor Attacks in Diffusion Models","created":"2024-07-31","cited_by_count":13,"area":"diffusion"},{"id":"2503.01323","title":"CacheQuant: Comprehensively Accelerated Diffusion Models","created":"2025-03-03","cited_by_count":13,"area":"diffusion"},{"id":"2505.14687","title":"Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers","created":"2025-05-20","cited_by_count":13,"area":"diffusion"},{"id":"2409.15557","title":"Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection","created":"2024-09-23","cited_by_count":12,"area":"diffusion"},{"id":"2505.05829","title":"Accelerating Diffusion Transformer via Increment-Calibrated Caching with Channel-Aware Singular Value Decomposition","created":"2025-05-09","cited_by_count":12,"area":"diffusion"},{"id":"2508.16984","title":"HiCache: A Plug-in Scaled-Hermite Upgrade for Taylor-Style Cache-then-Forecast Diffusion Acceleration","created":"2025-08-23","cited_by_count":12,"area":"diffusion"},{"id":"2404.05662","title":"BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models","created":"2024-04-08","cited_by_count":11,"area":"diffusion"},{"id":"2412.05926","title":"BiDM: Pushing the Limit of Quantization for Diffusion Models","created":"2024-12-08","cited_by_count":11,"area":"diffusion"},{"id":"2506.05096","title":"Astraea: A Token-wise Acceleration Framework for Video Diffusion Transformers","created":"2025-06-05","cited_by_count":11,"area":"diffusion"},{"id":"2506.08908","title":"SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware Skipping","created":"2025-06-10","cited_by_count":11,"area":null},{"id":"2404.09532","title":"TMPQ-DM: Joint Timestep Reduction and Quantization Precision Selection for Efficient Diffusion Models","created":"2024-04-15","cited_by_count":10,"area":"diffusion"},{"id":"2412.06028","title":"SparseDiT: Token Sparsification for Efficient Diffusion Transformer","created":"2024-12-08","cited_by_count":10,"area":"diffusion"},{"id":"2510.04188","title":"Let Features Decide Their Own Solvers: Hybrid Feature Caching for Diffusion Transformers","created":"2025-10-05","cited_by_count":10,"area":"diffusion"},{"id":"2510.11962","title":"MosaicDiff: Training-free Structural Pruning for Diffusion Model Acceleration Reflecting Pretraining Dynamics","created":"2025-10-13","cited_by_count":10,"area":"diffusion"},{"id":"2412.02852","title":"Learnable Sparsity for Vision Generative Models","created":"2024-12-03","cited_by_count":9,"area":"diffusion"},{"id":"2508.17588","title":"HERO: Hierarchical Extrapolation and Refresh for Efficient World Models","created":"2025-08-25","cited_by_count":9,"area":"wm"},{"id":"2404.14309","title":"Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective","created":"2024-04-22","cited_by_count":8,"area":"diffusion"},{"id":"2411.18375","title":"Individual Content and Motion Dynamics Preserved Pruning for Video Diffusion Models","created":"2024-11-27","cited_by_count":8,"area":"diffusion"},{"id":"2503.19897","title":"Scaling Down Text Encoders of Text-to-Image Diffusion Models","created":"2025-03-25","cited_by_count":8,"area":"diffusion"},{"id":"2509.25180","title":"DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space","created":"2025-09-29","cited_by_count":8,"area":"diffusion"},{"id":"2510.03012","title":"PocketSR: The Super-Resolution Expert in Your Pocket Mobiles","created":"2025-10-03","cited_by_count":8,"area":null},{"id":"2602.22654","title":"Denoising as Path Planning: Training-Free Acceleration of Diffusion Models with DPCache","created":"2026-02-26","cited_by_count":8,"area":"diffusion"},{"id":"2406.12837","title":"LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging","created":"2024-06-18","cited_by_count":7,"area":null},{"id":"2410.06664","title":"Decouple-Then-Merge: Finetune Diffusion Models as Multi-Task Learning","created":"2024-10-09","cited_by_count":7,"area":"diffusion"},{"id":"2509.00454","title":"Universal Properties of Activation Sparsity in Modern Large Language Models","created":"2025-08-30","cited_by_count":7,"area":null},{"id":"2602.05449","title":"DisCa: Accelerating Video Diffusion Transformers with Distillation-Compatible Learnable Feature Caching","created":"2026-02-05","cited_by_count":7,"area":"diffusion"},{"id":"2602.24208","title":"SenCache: Accelerating Diffusion Model Inference via Sensitivity-Aware Caching","created":"2026-02-27","cited_by_count":7,"area":"diffusion"},{"id":"2603.01623","title":"Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration","created":"2026-03-02","cited_by_count":7,"area":"diffusion"},{"id":"2404.14034","title":"PointDifformer: Robust Point Cloud Registration With Neural Diffusion and Transformer","created":"2024-04-22","cited_by_count":6,"area":null},{"id":"2503.15465","title":"FP4DiT: Towards Effective Floating Point Quantization for Diffusion Transformers","created":"2025-03-19","cited_by_count":6,"area":"diffusion"},{"id":"2505.05215","title":"Diffusion Model Quantization: A Review","created":"2025-05-08","cited_by_count":6,"area":"diffusion"},{"id":"2506.00329","title":"Foresight: Adaptive Layer Reuse for Accelerated and High-Quality Text-to-Video Generation","created":"2025-05-31","cited_by_count":6,"area":"diffusion"},{"id":"2510.25590","title":"RegionE: Adaptive Region-Aware Generation for Efficient Image Editing","created":"2025-10-29","cited_by_count":6,"area":null},{"id":"2603.22125","title":"DA-VAE: Plug-in Latent Compression for Diffusion via Detail Alignment","created":"2026-03-23","cited_by_count":6,"area":"diffusion"},{"id":"2311.03904","title":"RobustMat: Neural Diffusion for Street Landmark Patch Matching under Challenging Environments","created":"2023-11-07","cited_by_count":5,"area":null},{"id":"2312.04429","title":"Approximate Caching for Efficiently Serving Diffusion Models","created":"2023-12-07","cited_by_count":5,"area":"diffusion"},{"id":"2405.04834","title":"FlexEControl: Flexible and Efficient Multimodal Control for Text-to-Image Generation","created":"2024-05-08","cited_by_count":5,"area":"diffusion"},{"id":"2410.10166","title":"Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models","created":"2024-10-14","cited_by_count":5,"area":"diffusion"}],"next_cursor":"100"}