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This paper considers an efficient video modeling process called Video Latent Flow Matching (VLFM).
Ucf101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
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Auto-encoding variational bayes
Diederik P Kingma · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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On particle methods for parameter estimation in state-space models
Nikolas Kantas, Arnaud Doucet, Sumeetpal S. Singh, Jan Maciejowski, and Nicolas Chopin · 2015
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Youtube-8m: A large-scale video classification benchmark
Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, and Sudheendra Vijayanarasimhan · 2016
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The kinetics human action video dataset
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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A convergence theory for deep learning via over-parameterization
Zeyuan Allen-Zhu, Yuanzhi Li, and Zhao Song · 2019
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Transformer dissection: a unified understanding of transformer’s attention via the lens of kernel
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Are transformers universal approximators of sequence-to-sequence functions?
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J Reddi, and Sanjiv Kumar · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Hippo: Recurrent memory with optimal polynomial projections
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, and Christopher Ré · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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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 · 2020
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Research progress in attention mechanism in deep learning
Jian-wei LIU, Jun-wen LIU, and Xiong-lin LUO · 2021
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Moser flow: Divergence-based generative modeling on manifolds
Noam Rozen, Aditya Grover, Maximilian Nickel, and Yaron Lipman · 2021
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Does preprocessing help training over-parameterized neural networks?
Zhao Song, Shuo Yang, and Ruizhe Zhang · 2021
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Efficient attention: Attention with linear complexities
Zhuoran Shen, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, and Hongsheng Li · 2021
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Training (overparametrized) neural networks in near-linear time
Jan van den Brand, Binghui Peng, Zhao Song, and Omri Weinstein · 2021
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Building normalizing flows with stochastic interpolants
Michael S Albergo and Eric Vanden-Eijnden · 2022
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Matching normalizing flows and probability paths on manifolds
Heli Ben-Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Aditya Grover, Maximilian Nickel, Ricky TQ Chen, and Yaron Lipman · 2022
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ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Qinsheng Zhang, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, et al · 2022
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Training overparametrized neural networks in sublinear time
Yichuan Deng, Hang Hu, Zhao Song, Omri Weinstein, and Danyang Zhuo · 2022
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How to train your hippo: State space models with generalized orthogonal basis projections
Albert Gu, Isys Johnson, Aman Timalsina, Atri Rudra, and Christopher Ré · 2022
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Imagen video: High definition video generation with diffusion models
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik P Kingma, Ben Poole, Mohammad Norouzi, David J Fleet, et al · 2022
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Video diffusion models
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 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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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2022
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Bounding the width of neural networks via coupled initialization a worst case analysis
Alexander Munteanu, Simon Omlor, Zhao Song, and David Woodruff · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Make-a-video: Text-to-video generation without text-video data
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, et al · 2022
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Mcvd-masked conditional video diffusion for prediction, generation, and interpolation
Vikram Voleti, Alexia Jolicoeur-Martineau, and Chris Pal · 2022
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Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
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Magicvideo: Efficient video generation with latent diffusion models
Daquan Zhou, Weimin Wang, Hanshu Yan, Weiwei Lv, Yizhe Zhu, and Jiashi Feng · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Bypass exponential time preprocessing: Fast neural network training via weight-data correlation preprocessing
Josh Alman, Zhao Song, Ruizhe Zhang, and Danyang Zhuo · 2023
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Physics of language models: Part 1, context-free grammar
Zeyuan Allen-Zhu and Yuanzhi Li · 2023
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Latent-shift: Latent diffusion with temporal shift for efficient text-to-video generation
Jie An, Songyang Zhang, Harry Yang, Sonal Gupta, Jia-Bin Huang, Jiebo Luo, and Xi Yin · 2023
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Align your latents: High-resolution video synthesis with latent diffusion models
Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, and Karsten Kreis · 2023
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Algorithm and hardness for dynamic attention maintenance in large language models
Jan van den Brand, Zhao Song, and Tianyi Zhou · 2023
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Score approximation, estimation and distribution recovery of diffusion models on low-dimensional data
Minshuo Chen, Kaixuan Huang, Tuo Zhao, and Mengdi Wang · 2023
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Toward infinite-long prefix in transformer
Jiuxiang Gu, Yingyu Liang, Zhenmei Shi, Zhao Song, and Chiwun Yang · 2024
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Itai Gat, Tal Remez, Neta Shaul, Felix Kreuk, Ricky TQ Chen, Gabriel Synnaeve, Yossi Adi, and Yaron Lipman · 2024
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Outlier-efficient hopfield layers for large transformer-based models
Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Robin Luo, Hong-Yu Chen, Weijian Li, Wei-Po Wang, and Han Liu · 2024
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On computational limits of modern hopfield models: A fine-grained complexity analysis
Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, and Han Liu · 2024
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Sequence-augmented se (3)-flow matching for conditional protein backbone generation
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Yichuan Deng, Zhihang Li, and Zhao Song · 2023
Cited alongside, same era.
Unmasking transformers: A theoretical approach to data recovery via attention weights
Yichuan Deng, Zhao Song, Shenghao Xie, and Chiwun Yang · 2023
Cited alongside, same era.
Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu and Tri Dao · 2023
Cited alongside, same era.
Preserve your own correlation: A noise prior for video diffusion models
Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, and Yogesh Balaji · 2023
Cited alongside, same era.
Yeqi Gao, Zhao Song, Weixin Wang, and Junze Yin · 2023
Cited alongside, same era.
Reuse and diffuse: Iterative denoising for text-to-video generation
Jiaxi Gu, Shicong Wang, Haoyu Zhao, Tianyi Lu, Xing Zhang, Zuxuan Wu, Songcen Xu, Wei Zhang, Yu-Gang Jiang, and Hang Xu · 2023
Cited alongside, same era.
Animatediff: Animate your personalized text-to-image diffusion models without specific tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao, Zhengyang Liang, Yaohui Wang, Yu Qiao, Maneesh Agrawala, Dahua Lin, and Bo Dai · 2023
Cited alongside, same era.
Iterative α \alpha -(de) blending: A minimalist deterministic diffusion model
Eric Heitz, Laurent Belcour, and Thomas Chambon · 2023
Cited alongside, same era.
Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael Bronstein, et al · 2024
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Fundamental limits of prompt tuning transformers: Universality, capacity and efficiency
Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, and Han Liu · 2024
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Jerry Yao-Chieh Hu, Dennis Wu, and Han Liu · 2024
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On statistical rates and provably efficient criteria of latent diffusion transformers (dits)
Jerry Yao-Chieh Hu, Weimin Wu, Zhao Song, and Han Liu · 2024
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Miradata: A large-scale video dataset with long durations and structured captions
Xuan Ju, Yiming Gao, Zhaoyang Zhang, Ziyang Yuan, Xintao Wang, Ailing Zeng, Yu Xiong, Qiang Xu, and Ying Shan · 2024
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Pyramidal flow matching for efficient video generative modeling
Yang Jin, Zhicheng Sun, Ningyuan Li, Kun Xu, Hao Jiang, Nan Zhuang, Quzhe Huang, Yang Song, Yadong Mu, and Zhouchen Lin · 2024
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Yekun Ke, Yingyu Liang, Zhenmei Shi, Zhao Song, and Chiwun Yang · 2024
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Hunyuanvideo: A systematic framework for large video generative models
Weijie Kong, Qi Tian, Zijian Zhang, Rox Min, Zuozhuo Dai, Jin Zhou, Jiangfeng Xiong, Xin Li, Bo Wu, Jianwei Zhang, et al · 2024
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Aixin Liu, Bei Feng, Bing Xue, Bingxuan Wang, Bochao Wu, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, et al · 2024
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Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song, and Tianyi Zhou · 2024
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Fine-grained attention i/o complexity: Comprehensive analysis for backward passes
Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song, and Yufa Zhou · 2024
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Yingyu Liang, Heshan Liu, Zhenmei Shi, Zhao Song, Zhuoyan Xu, and Junze Yin · 2024
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Beyond linear approximations: A novel pruning approach for attention matrix
Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song, and Yufa Zhou · 2024
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A tighter complexity analysis of sparsegpt
Xiaoyu Li, Yingyu Liang, Zhenmei Shi, and Zhao Song · 2024
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Looped relu mlps may be all you need as practical programmable computers
Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, and Yufa Zhou · 2024
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Multi-layer transformers gradient can be approximated in almost linear time
Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, and Yufa Zhou · 2024
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Tensor attention training: Provably efficient learning of higher-order transformers
Yingyu Liang, Zhenmei Shi, Zhao Song, and Yufa Zhou · 2024
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Voicebox: Text-guided multilingual universal speech generation at scale
Matthew Le, Apoorv Vyas, Bowen Shi, Brian Karrer, Leda Sari, Rashel Moritz, Mary Williamson, Vimal Manohar, Yossi Adi, Jay Mahadeokar, et al · 2024
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U-mamba: Enhancing long-range dependency for biomedical image segmentation
Jun Ma, Feifei Li, and Bo Wang · 2024
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Openvid-1m: A large-scale high-quality dataset for text-to-video generation
Kepan Nan, Rui Xie, Penghao Zhou, Tiehan Fan, Zhenheng Yang, Zhijie Chen, Xiang Li, Jian Yang, and Ying Tai · 2024
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Movie gen: A cast of media foundation models
Adam Polyak, Amit Zohar, Andrew Brown, Andros Tjandra, Animesh Sinha, Ann Lee, Apoorv Vyas, Bowen Shi, Chih-Yao Ma, Ching-Yao Chuang, et al · 2024
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Vm-unet: Vision mamba unet for medical image segmentation
Jiacheng Ruan and Suncheng Xiang · 2024
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Learning to (learn at test time): Rnns with expressive hidden states
Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram, Genghan Zhang, Yann Dubois, Xinlei Chen, Xiaolong Wang, Sanmi Koyejo, et al · 2024
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Zhenmei Shi, Yifei Ming, Xuan-Phi Nguyen, Yingyu Liang, and Shafiq Joty · 2024
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Solving attention kernel regression problem via pre-conditioner
Zhao Song, Junze Yin, and Lichen Zhang · 2024
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Training multi-layer over-parametrized neural network in subquadratic time
Zhao Song, Lichen Zhang, and Ruizhe Zhang · 2024
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Visual autoregressive modeling: Scalable image generation via next-scale prediction
Keyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng, and Liwei Wang · 2024
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Uniform memory retrieval with larger capacity for modern hopfield models
Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao, and Han Liu · 2024
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Transformers are deep optimizers: Provable in-context learning for deep model training
Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu, Zhao Song, and Han Liu · 2024
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Do large language models have compositional ability? an investigation into limitations and scalability
Zhuoyan Xu, Zhenmei Shi, and Yingyu Liang · 2024
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Towards few-shot adaptation of foundation models via multitask finetuning
Zhuoyan Xu, Zhenmei Shi, Junyi Wei, Fangzhou Mu, Yin Li, and Yingyu Liang · 2024
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Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation
Zhaohu Xing, Tian Ye, Yijun Yang, Guang Liu, and Lei Zhu · 2024
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Vision mamba: Efficient visual representation learning with bidirectional state space model
Lianghui Zhu, Bencheng Liao, Qian Zhang, Xinlong Wang, Wenyu Liu, and Xinggang Wang · 2024
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Open-sora: Democratizing efficient video production for all
Zangwei Zheng, Xiangyu Peng, Tianji Yang, Chenhui Shen, Shenggui Li, Hongxin Liu, Yukun Zhou, Tianyi Li, and Yang You · 2024
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