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We investigate the statistical and computational limits of latent Diffusion Transformers (DiTs) under the low-dimensional linear latent space assumption.
On the complexity of k-sat
Russell Impagliazzo and Ramamohan Paturi · 2001
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Distribution approximation and statistical estimation guarantees of generative adversarial networks
Minshuo Chen, Wenjing Liao, Hongyuan Zha, and Tuo Zhao · 2002
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On problems as hard as cnf-sat
Marek Cygan, Holger Dell, Daniel Lokshtanov, Dániel Marx, Jesper Nederlof, Yoshio Okamoto, Ramamohan Paturi, Saket Saurabh, and Magnus Wahlström · 2016
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Sketching for kronecker product regression and p-splines
Huaian Diao, Zhao Song, Wen Sun, and David Woodruff · 2018
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Learning low-dimensional temporal representations
Bing Su and Ying Wu · 2018
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On some fine-grained questions in algorithms and complexity
Virginia Vassilevska Williams · 2018
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Optimal sketching for kronecker product regression and low rank approximation
Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, and David Woodruff · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 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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Gpt-3: Its nature, scope, limits, and consequences
Luciano Floridi and Massimo Chiriatti · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Hopfield networks is all you need
Hubert Ramsauer, Bernhard Schafl, Johannes Lehner, Philipp Seidl, Michael Widrich, Thomas Adler, Lukas Gruber, Markus Holzleitner, Milena Pavlovic, Geir Kjetil Sandve, et al · 2020
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Are transformers universal approximators of sequence-to-sequence functions?
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank Reddi, and Sanjiv Kumar · 2020
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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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Dnabert: pre-trained bidirectional encoder representations from transformers model for dna-language in genome
Yanrong Ji, Zhihan Zhou, Han Liu, and Ramana V Davuluri · 2021
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Robust sparse low-rank embedding for image dimension reduction
Zhonghua Liu, Yue Lu, Zhihui Lai, Weihua Ou, and Kaibing Zhang · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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The intrinsic dimension of images and its impact on learning
Phillip Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, and Tom Goldstein · 2021
Cited alongside, same era.
Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz · 2021
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All are worth words: a vit backbone for score-based diffusion models
Fan Bao, Chongxuan Li, Yue Cao, and Jun Zhu · 2022
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Convergence of denoising diffusion models under the manifold hypothesis
Valentin De Bortoli · 2022
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Inductive biases and variable creation in self-attention mechanisms
Benjamin L Edelman, Surbhi Goel, Sham Kakade, and Cyril Zhang · 2022
Cited alongside, same era.
Provable memorization capacity of transformers
Dit-3d: Exploring plain diffusion transformers for 3d shape generation
Shentong Mo, Enze Xie, Ruihang Chu, Lanqing Hong, Matthias Niessner, and Zhenguo Li · 2023
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Diffusion models are minimax optimal distribution estimators
Kazusato Oko, Shunta Akiyama, and Taiji Suzuki · 2023
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Universality and limitations of prompt tuning
Yihan Wang, Jatin Chauhan, Wei Wang, and Cho-Jui Hsieh · 2023
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Fast training of diffusion models with masked transformers
Hongkai Zheng, Weili Nie, Arash Vahdat, and Anima Anandkumar · 2023
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Dnabert-2: Efficient foundation model and benchmark for multi-species genome
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Junghwan Kim, Michelle Kim, and Barzan Mozafari · 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.
Fast attention requires bounded entries
Josh Alman and Zhao Song · 2023
Cited alongside, same era.
In search of dispersed memories: Generative diffusion models are associative memory networks
Luca Ambrogioni · 2023
Cited alongside, same era.
Score approximation, estimation and distribution recovery of diffusion models on low-dimensional data
Minshuo Chen, Kaixuan Huang, Tuo Zhao, and Mengdi Wang · 2023
Cited alongside, same era.
Benjamin Hoover, Hendrik Strobelt, Dmitry Krotov, Judy Hoffman, Zsolt Kira, and Duen Horng Chau · 2023
Cited alongside, same era.
Zhihan Zhou, Yanrong Ji, Weijian Li, Pratik Dutta, Ramana Davuluri, and Han Liu · 2023
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Sample complexity bounds for score-matching: Causal discovery and generative modeling
Zhenyu Zhu, Francesco Locatello, and Volkan Cevher · 2023
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Losing dimensions: Geometric memorization in generative diffusion
Beatrice Achilli, Enrico Ventura, Gianluigi Silvestri, Bao Pham, Gabriel Raya, Dmitry Krotov, Carlo Lucibello, and Luca Ambrogioni · 2024
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Nearly d-linear convergence bounds for diffusion models via stochastic localization
Joe Benton, Valentin De Bortoli, Arnaud Doucet, and George Deligiannidis · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
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Tensor attention training: Provably efficient learning of higher-order transformers
Jiuxiang Gu, Yingyu Liang, Zhenmei Shi, Zhao Song, and Yufa Zhou · 2024
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Decompdiff: diffusion models with decomposed priors for structure-based drug design
Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, and Quanquan Gu · 2024
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Sora: A review on background, technology, limitations, and opportunities of large vision models, 2024
Yixin Liu, Kai Zhang, Yuan Li, Zhiling Yan, Chujie Gao, Ruoxi Chen, Zhengqing Yuan, Yue Huang, Hanchi Sun, Jianfeng Gao, Lifang He, and Lichao Sun · 2024
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Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers
Nanye Ma, Mark Goldstein, Michael S Albergo, Nicholas M Boffi, Eric Vanden-Eijnden, and Saining Xie · 2024
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Sora: A video generative model based on transformer diffusion
OpenAI · 2024
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Score-based diffusion models via stochastic differential equations–a technical tutorial
Wenpin Tang and Hanyang Zhao · 2024
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Optimal score estimation via empirical bayes smoothing
Andre Wibisono, Yihong Wu, and Kaylee Yingxi Yang · 2024
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