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Diffusion models have emerged as powerful generative models capable of producing high-quality contents such as images, videos, and audio, demonstrating their potential to revolutionize digital content creation.
Estimation of non-normalized statistical models by score matching
Aapo Hyvärinen and Peter Dayan · 2005
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Multistep methods for sdes and their application to problems with small noise
Evelyn Buckwar and Renate Winkler · 2006
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The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al · 2009
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Exponential integrators
Marlis Hochbruck and Alexander Ostermann · 2010
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2010
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2011
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Anderson acceleration for fixed-point iterations
Homer F Walker and Peng Ni · 2011
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Wasserstein barycenter and its application to texture mixing
Julien Rabin, Gabriel Peyré, Julie Delon, and Marc Bernot · 2012
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Auto-encoding variational bayes, 2013
Diederik P Kingma, Max Welling, et al · 2013
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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Neural ordinary differential equations
Ricky TQ Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
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Learned step size quantization
Steven K Esser, Jeffrey L McKinstry, Deepika Bablani, Rathinakumar Appuswamy, and Dharmendra S Modha · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Wavegrad: Estimating gradients for waveform generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J Weiss, Mohammad Norouzi, and William Chan · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Diffwave: A versatile diffusion model for audio synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2020
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Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, and Yuxiong He · 2020
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Score-based generative modeling with critically-damped langevin diffusion
Tim Dockhorn, Arash Vahdat, and Karsten Kreis · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Gotta go fast when generating data with score-based models
Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, and Ioannis Mitliagkas · 2021
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On fast sampling of diffusion probabilistic models
Zhifeng Kong and Wei Ping · 2021
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Priorgrad: Improving conditional denoising diffusion models with data-dependent adaptive prior
Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, and Tie-Yan Liu · 2021
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Brecq: Pushing the limit of post-training quantization by block reconstruction
Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang, Fengwei Yu, Wei Wang, and Shi Gu · 2021
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Knowledge distillation in iterative generative models for improved sampling speed
Eric Luhman and Troy Luhman · 2021
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Consistent accelerated inference via confident adaptive transformers
Tal Schuster, Adam Fisch, Tommi Jaakkola, and Regina Barzilay · 2021
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Maximum likelihood training of score-based diffusion models
Yang Song, Conor Durkan, Iain Murray, and Stefano Ermon · 2021
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Learning to efficiently sample from diffusion probabilistic models
Daniel Watson, Jonathan Ho, Mohammad Norouzi, and William Chan · 2021
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Oneflow: Redesign the distributed deep learning framework from scratch
Jinhui Yuan, Xinqi Li, Cheng Cheng, Juncheng Liu, Ran Guo, Shenghang Cai, Chi Yao, Fei Yang, Xiaodong Yi, Chuan Wu, et al · 2021
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Diffusion normalizing flow
Qinsheng Zhang and Yongxin Chen · 2021
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Semi-parametric neural image synthesis
Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas Müller, and Björn Ommer · 2022
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Onediff: An out-of-the-box acceleration library for diffusion models
OneDiff Contributors · 2022
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Diffedit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord · 2022
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Flashattention: Fast and memory-efficient exact attention with io-awareness
Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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Diffuseq: Sequence to sequence text generation with diffusion models
Shansan Gong, Mukai Li, Jiangtao Feng, Zhiyong Wu, and LingPeng Kong · 2022
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Latent video diffusion models for high-fidelity long video generation
Yingqing He, Tianyu Yang, Yong Zhang, Ying Shan, and Qifeng Chen · 2022
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Denoising mcmc for accelerating diffusion-based generative models
Beomsu Kim and Jong Chul Ye · 2022
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xformers: A modular and hackable transformer modelling library
Benjamin Lefaudeux, Francisco Massa, Diana Liskovich, Wenhan Xiong, Vittorio Caggiano, Sean Naren, Min Xu, Jieru Hu, Marta Tintore, Susan Zhang, Patrick Labatut, Daniel Haziza, Luca Wehrstedt, Jeremy Reizenstein, and Grigory Sizov · 2022
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Diffusion-lm improves controllable text generation
Xiang Li, John Thickstun, Ishaan Gulrajani, Percy S Liang, and Tatsunori B Hashimoto · 2022
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Flow matching for generative modeling
Yaron Lipman, Ricky TQ Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2022
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Rectified flow: A marginal preserving approach to optimal transport
Qiang Liu · 2022
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Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
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Deep equilibrium approaches to diffusion models
Ashwini Pokle, Zhengyang Geng, and J Zico Kolter · 2022
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
Cited alongside, same era.
knn-diffusion: Image generation via large-scale retrieval
Shelly Sheynin, Oron Ashual, Adam Polyak, Uriel Singer, Oran Gafni, Eliya Nachmani, and Yaniv Taigman · 2022
Cited alongside, same era.
An overview of diffusion models: Applications, guided generation, statistical rates and optimization
Minshuo Chen, Song Mei, Jianqing Fan, and Mengdi Wang · 2024
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Stable fast
chengzeyi · 2024
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A survey on diffusion models for inverse problems, 2024
Giannis Daras, Hyungjin Chung, Chieh-Hsin Lai, Yuki Mitsufuji, Jong Chul Ye, Peyman Milanfar, Alexandros G. Dimakis, and Mauricio Delbracio · 2024
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3d paintbrush: Local stylization of 3d shapes with cascaded score distillation
Dale Decatur, Itai Lang, Kfir Aberman, and Rana Hanocka · 2024
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer · 2024
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Anwaar Ulhaq, Naveed Akhtar, and Ganna Pogrebna · 2022
Cited alongside, same era.
Digress: Discrete denoising diffusion for graph generation
Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, and Pascal Frossard · 2022
Cited alongside, same era.
Fast sampling of diffusion models with exponential integrator
Qinsheng Zhang and Yongxin Chen · 2022
Cited alongside, same era.
Magicvideo: Efficient video generation with latent diffusion models
Daquan Zhou, Weimin Wang, Hanshu Yan, Weiwei Lv, Yizhe Zhu, and Jiashi Feng · 2022
Cited alongside, same era.
Stochastic interpolants: A unifying framework for flows and diffusions
Michael S Albergo, Nicholas M Boffi, and Eric Vanden-Eijnden · 2023
Cited alongside, same era.
All are worth words: A vit backbone for diffusion models
Fan Bao, Shen Nie, Kaiwen Xue, Yue Cao, Chongxuan Li, Hang Su, and Jun Zhu · 2023
Cited alongside, same era.
Memory-efficient 3d denoising diffusion models for medical image processing
Florentin Bieder, Julia Wolleb, Alicia Durrer, Robin Sandkuehler, and Philippe C Cattin · 2023
Cited alongside, same era.
Bi’an Du, Wei Hu, and Renjie Liao · 2024
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A unified sequence parallelism approach for long context generative ai
Jiarui Fang and Shangchun Zhao · 2024
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Diffusion meets flow matching: Two sides of the same coin
Ruiqi Gao, Emiel Hoogeboom, Jonathan Heek, Valentin De Bortoli, Kevin P. Murphy, and Tim Salimans · 2024
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Mix-of-show: Decentralized low-rank adaptation for multi-concept customization of diffusion models
Yuchao Gu, Xintao Wang, Jay Zhangjie Wu, Yujun Shi, Yunpeng Chen, Zihan Fan, Wuyou Xiao, Rui Zhao, Shuning Chang, Weijia Wu, et al · 2024
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Gaussian mixture solvers for diffusion models
Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, and Chongxuan Li · 2024
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Improved noise schedule for diffusion training
Tiankai Hang and Shuyang Gu · 2024
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Ptqd: Accurate post-training quantization for diffusion models
Yefei He, Luping Liu, Jing Liu, Weijia Wu, Hong Zhou, and Bohan Zhuang · 2024
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Latent diffusion models for controllable rna sequence generation
Kaixuan Huang, Yukang Yang, Kaidi Fu, Yanyi Chu, Le Cong, and Mengdi Wang · 2024
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Scenediffuser: Efficient and controllable driving simulation initialization and rollout
Max Jiang, Yijing Bai, Andre Cornman, Christopher Davis, Xiukun Huang, Hong Jeon, Sakshum Kulshrestha, John Lambert, Shuangyu Li, Xuanyu Zhou, et al · 2024
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Latent diffusion for language generation
Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shekhtman, and Kilian Q Weinberger · 2024
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Simplifying, stabilizing and scaling continuous-time consistency models
Cheng Lu and Yang Song · 2024
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Diff-instruct: A universal approach for transferring knowledge from pre-trained diffusion models
Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, and Zhihua Zhang · 2024
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Video diffusion models: A survey
Andrew Melnik, Michal Ljubljanac, Cong Lu, Qi Yan, Weiming Ren, and Helge Ritter · 2024
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Efficient 3d shape generation via diffusion mamba with bidirectional ssms
Shentong Mo · 2024
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T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models
Chong Mou, Xintao Wang, Liangbin Xie, Yanze Wu, Jian Zhang, Zhongang Qi, and Ying Shan · 2024
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L3dg: Latent 3d gaussian diffusion
Barbara Roessle, Norman Müller, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, Angela Dai, and Matthias Nießner · 2024
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Align your steps: Optimizing sampling schedules in diffusion models
Amirmojtaba Sabour, Sanja Fidler, and Karsten Kreis · 2024
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Fora: Fast-forward caching in diffusion transformer acceleration
Pratheba Selvaraju, Tianyu Ding, Tianyi Chen, Ilya Zharkov, and Luming Liang · 2024
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Parallel sampling of diffusion models
Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, and Nima Anari · 2024
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Temporal dynamic quantization for diffusion models
Junhyuk So, Jungwon Lee, Daehyun Ahn, Hyungjun Kim, and Eunhyeok Park · 2024
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Unveiling redundancy in diffusion transformers (dits): A systematic study
Xibo Sun, Jiarui Fang, Aoyu Li, and Jinzhe Pan · 2024
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Accelerating parallel sampling of diffusion models
Zhiwei Tang, Jiasheng Tang, Hao Luo, Fan Wang, and Tsung-Hui Chang · 2024
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Diffusionpipe: Training large diffusion models with efficient pipelines, 2024
Ye Tian, Zhen Jia, Ziyue Luo, Yida Wang, and Chuan Wu · 2024
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Cache me if you can: Accelerating diffusion models through block caching
Felix Wimbauer, Bichen Wu, Edgar Schoenfeld, Xiaoliang Dai, Ji Hou, Zijian He, Artsiom Sanakoyeu, Peizhao Zhang, Sam Tsai, Jonas Kohler, et al · 2024
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Consistent3d: Towards consistent high-fidelity text-to-3d generation with deterministic sampling prior
Zike Wu, Pan Zhou, Xuanyu Yi, Xiaoding Yuan, and Hanwang Zhang · 2024
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Simda: Simple diffusion adapter for efficient video generation
Zhen Xing, Qi Dai, Han Hu, Zuxuan Wu, and Yu-Gang Jiang · 2024
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Perflow: Piecewise rectified flow as universal plug-and-play accelerator
Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, and Jiashi Feng · 2024
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Yang Yang, Wen Wang, Liang Peng, Chaotian Song, Yao Chen, Hengjia Li, Xiaolong Yang, Qinglin Lu, Deng Cai, Boxi Wu, et al · 2024
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One-step diffusion with distribution matching distillation
Tianwei Yin, Michaël Gharbi, Richard Zhang, Eli Shechtman, Fredo Durand, William T Freeman, and Taesung Park · 2024
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Latent 3d graph diffusion
Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, and Yang Shen · 2024
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Text diffusion model with encoder-decoder transformers for sequence-to-sequence generation
Hongyi Yuan, Zheng Yuan, Chuanqi Tan, Fei Huang, and Songfang Huang · 2024
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Resshift: Efficient diffusion model for image super-resolution by residual shifting
Zongsheng Yue, Jianyi Wang, and Chen Change Loy · 2024
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Uni-controlnet: All-in-one control to text-to-image diffusion models
Shihao Zhao, Dongdong Chen, Yen-Chun Chen, Jianmin Bao, Shaozhe Hao, Lu Yuan, and Kwan-Yee K Wong · 2024
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Slimflow: Training smaller one-step diffusion models with rectified flow
Yuanzhi Zhu, Xingchao Liu, and Qiang Liu · 2024
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Block diffusion: Interpolating between autoregressive and diffusion language models
Marianne Arriola, Aaron Gokaslan, Justin T Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, and Volodymyr Kuleshov · 2025
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Sana-sprint: One-step diffusion with continuous-time consistency distillation
Junsong Chen, Shuchen Xue, Yuyang Zhao, Jincheng Yu, Sayak Paul, Junyu Chen, Han Cai, Enze Xie, and Song Han · 2025
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Efficient-vdit: Efficient video diffusion transformers with attention tile
Hangliang Ding, Dacheng Li, Runlong Su, Peiyuan Zhang, Zhijie Deng, Ion Stoica, and Hao Zhang · 2025
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Yuxiang Fu, Qi Yan, Lele Wang, Ke Li, and Renjie Liao · 2025
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Controlnet++: Improving conditional controls with efficient consistency feedback
Ming Li, Taojiannan Yang, Huafeng Kuang, Jie Wu, Zhaoning Wang, Xuefeng Xiao, and Chen Chen · 2025
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Diffusion models without classifier-free guidance
Zhicong Tang, Jianmin Bao, Dong Chen, and Baining Guo · 2025
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Training-free and adaptive sparse attention for efficient long video generation
Yifei Xia, Suhan Ling, Fangcheng Fu, Yujie Wang, Huixia Li, Xuefeng Xiao, and Bin Cui · 2025
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Reconstruction vs. generation: Taming optimization dilemma in latent diffusion models
Jingfeng Yao, Bin Yang, and Xinggang Wang · 2025
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