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One-step shortcut diffusion models [Frans, Hafner, Levine and Abbeel, ICLR 2025] have shown potential in vision generation, but their reliance on first-order trajectory supervision is fundamentally limited.
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Atomft: solving odes and daes using taylor series
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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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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Attention is all you need
A Vaswani · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 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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Ffjord: Free-form continuous dynamics for scalable reversible generative models
Will Grathwohl, Ricky TQ Chen, Jesse Bettencourt, Ilya Sutskever, and David Duvenaud · 2018
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Efficient neural audio synthesis
Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aaron Oord, Sander Dieleman, and Koray Kavukcuoglu · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Adaptivity of deep relu network for learning in besov and mixed smooth besov spaces: optimal rate and curse of dimensionality
Taiji Suzuki · 2019
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How to train your neural ODE: the world of Jacobian and kinetic regularization
Chris Finlay, Jörn-Henrik Jacobsen, Levon Nurbekyan, and Adam Oberman · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Learning differential equations that are easy to solve
Jacob Kelly, Jesse Bettencourt, Matthew J Johnson, and David K Duvenaud · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen · 2021
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Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant · 2021
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Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang · 2021
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Show your work: Scratchpads for intermediate computation with language models
Maxwell Nye, Anders Johan Andreassen, Gur AriGuy, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, et al · 2021
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Calibrate before use: Improving few-shot performance of language models
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh · 2021
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2022
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Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot, and Ufuk Topcu · 2022
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A nearly optimal size coreset algorithm with nearly linear time
Yichuan Deng, Zhao Song, Yitan Wang, and Yuanyuan Yang · 2022
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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 · 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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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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Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
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Cross-task generalization via natural language crowdsourcing instructions
Swaroop Mishra, Daniel Khashabi, Chitta Baral, and Hannaneh Hajishirzi · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 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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Black-box tuning for language-model-as-a-service
Tianxiang Sun, Yunfan Shao, Hong Qian, Xuanjing Huang, and Xipeng Qiu · 2022
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Gmflow: Learning optical flow via global matching
Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, and Dacheng Tao · 2022
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Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
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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
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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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Federated empirical risk minimization via second-order method
Song Bian, Zhao Song, and Junze Yin · 2023
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Latent diffusion transformer for probabilistic time series forecasting
Shibo Feng, Chunyan Miao, Zhong Zhang, and Peilin Zhao · 2024
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Flow matching achieves minimax optimal convergence
Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, and Masanori Koyama · 2024
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Improved noise schedule for diffusion training
Tiankai Hang and Shuyang Gu · 2024
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Flow matching for conditional text generation in a few sampling steps
Vincent Hu, Di Wu, Yuki Asano, Pascal Mettes, Basura Fernando, Björn Ommer, and Cees Snoek · 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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Ting Chen · 2023
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Yichuan Deng, Sridhar Mahadevan, and Zhao Song · 2023
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Flow matching for scalable simulation-based inference
Maximilian Dax, Jonas Wildberger, Simon Buchholz, Stephen R Green, Jakob H Macke, and Bernhard Scholkopf · 2023
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Llama-adapter v2: Parameter-efficient visual instruction model
Peng Gao, Jiaming Han, Renrui Zhang, Ziyi Lin, Shijie Geng, Aojun Zhou, Wei Zhang, Pan Lu, Conghui He, Xiangyu Yue, et al · 2023
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An over-parameterized exponential regression
Yeqi Gao, Sridhar Mahadevan, and Zhao Song · 2023
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Yeqi Gao, Zhao Song, Weixin Wang, and Junze Yin · 2023
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Gradientcoin: A peer-to-peer decentralized large language models
Yeqi Gao, Zhao Song, and Junze Yin · 2023
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An iterative algorithm for rescaled hyperbolic functions regression
Yeqi Gao, Zhao Song, and Junze Yin · 2023
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Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, 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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Equivariant flow matching
Leon Klein, Andreas Kramer, and Frank Noe · 2024
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Yekun Ke, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, and Zhao Song · 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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Common diffusion noise schedules and sample steps are flawed
Shanchuan Lin, Bingchen Liu, Jiashi Li, and Xiao Yang · 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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Beyond linear approximations: A novel pruning approach for attention matrix, 2024
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A tighter complexity analysis of sparsegpt
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Fast second-order method for neural network under small treewidth setting
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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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Differential privacy mechanisms in neural tangent kernel regression
Yingyu Liang, Zhizhou Sha, Zhenmei Shi, and Zhao Song · 2024
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Unraveling the smoothness properties of diffusion models: A gaussian mixture perspective
Yingyu Liang, Zhenmei Shi, Zhao Song, and Yufa Zhou · 2024
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Quantum speedups for approximating the john ellipsoid
Xiaoyu Li, Zhao Song, and Junwei Yu · 2024
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Diff-foley: Synchronized video-to-audio synthesis with latent diffusion models
Simian Luo, Chuanhao Yan, Chenxu Hu, and Hang Zhao · 2024
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Score-based generative diffusion models for social recommendations
Chengyi Liu, Jiahao Zhang, Shijie Wang, Wenqi Fan, and Qing Li · 2024
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Introducing ChatGPT, 2024
OpenAI · 2024
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Beyond first-order tweedie: Solving inverse problems using latent diffusion
Litu Rout, Yujia Chen, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, and Wen-Sheng Chu · 2024
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Lazydit: Lazy learning for the acceleration of diffusion transformers
Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Yanyu Li, Yifan Gong, Kai Zhang, Hao Tan, Jason Kuen, Henghui Ding, et al · 2024
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Lazydit: Lazy learning for the acceleration of diffusion transformers
Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Yanyu Li, Yifan Gong, Kai Zhang, Hao Tan, Jason Kuen, Henghui Ding, et al · 2024
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Numerical pruning for efficient autoregressive models
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Numerical pruning for efficient autoregressive models
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An investigation of noise robustness for flow-matching-based zero-shot tts
Xiaofei Wang, Sefik Emre Eskimez, Manthan Thakker, Hemin Yang, Zirun Zhu, Min Tang, Yufei Xia, Jinzhu Li, Sheng Zhao, Jinyu Li, et al · 2024
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Omnicontrolnet: Dual-stage integration for conditional image generation
Yilin Wang, Haiyang Xu, Xiang Zhang, Zeyuan Chen, Zhizhou Sha, Zirui Wang, and Zhuowen Tu · 2024
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Towards few-shot adaptation of foundation models via multitask finetuning
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Dissecting submission limit in desk-rejections: A mathematical analysis of fairness in ai conference policies
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Nrflow: Towards noise-robust generative modeling via second-order flow matching
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One step diffusion via shortcut models
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