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Understanding the expressive ability of a specific model is essential for grasping its capacity limitations.
Time, hardware, and uniformity
D Mix Barrington and Neil Immerman · 1994
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Uniform constant-depth threshold circuits for division and iterated multiplication
William Hesse, Eric Allender, and David A Mix Barrington · 2002
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Computational complexity: a modern approach
Sanjeev Arora and Boaz Barak · 2009
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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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Tutorial on variational autoencoders
Carl Doersch · 2016
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Conditional image generation with pixelcnn decoders
Aaron Van den Oord, Nal Kalchbrenner, Lasse Espeholt, Oriol Vinyals, Alex Graves, et al · 2016
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Pixelsnail: An improved autoregressive generative model
Xi Chen, Nikhil Mishra, Mostafa Rohaninejad, and Pieter Abbeel · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Durk P Kingma and Prafulla Dhariwal · 2018
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Image transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
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An analysis of encoder representations in transformer-based machine translation
Alessandro Raganato and Jörg Tiedemann · 2018
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On the turing completeness of modern neural network architectures
Jorge Pérez, Javier Marinković, and Pablo Barceló · 2019
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Generating diverse high-fidelity images with vq-vae-2
Ali Razavi, Aaron Van den Oord, and Oriol Vinyals · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Learning deep transformer models for machine translation
Qiang Wang, Bei Li, Tong Xiao, Jingbo Zhu, Changliang Li, Derek F Wong, and Lidia S Chao · 2019
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Theoretical limitations of self-attention in neural sequence models
Michael Hahn · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Crea. blender: a neural network-based image generation game to assess creativity
Janet Rafner, Arthur Hjorth, Sebastian Risi, Lotte Philipsen, Charles Dumas, Michael Mose Biskjær, Lior Noy, Kristian Tylén, Carsten Bergenholtz, Jesse Lynch, et al · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Multimodal transformer for multimodal machine translation
Shaowei Yao and Xiaojun Wan · 2020
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Cogview: Mastering text-to-image generation via transformers
Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, et al · 2021
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
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Formal language recognition by hard attention transformers: Perspectives from circuit complexity
Yiding Hao, Dana Angluin, and Robert Frank · 2022
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Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans · 2022
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Transformers learn shortcuts to automata
Bingbin Liu, Jordan T Ash, Surbhi Goel, Akshay Krishnamurthy, and Cyril Zhang · 2022
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Autoregressive image generation using residual quantization
Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, and Wook-Shin Han · 2022
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A fast ode solver for diffusion probabilistic model sampling in around 10 steps
C Lu, Y Zhou, F Bao, J Chen, and C Li · 2022
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Provably optimal memory capacity for modern hopfield models: Transformer-compatible dense associative memories as spherical codes
Jerry Yao-Chieh Hu, Dennis Wu, and Han Liu · 2024
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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, Zhuoru Li, Sophia Pi, , Zhao Song, and Han Liu · 2024
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Yekun Ke, Yingyu Liang, Zhenmei Shi, Zhao Song, and Chiwun Yang · 2024
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U-kan makes strong backbone for medical image segmentation and generation
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Saturated transformers are constant-depth threshold circuits
William Merrill, Ashish Sabharwal, and Noah A Smith · 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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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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The parallelism tradeoff: Limitations of log-precision transformers
William Merrill and Ashish Sabharwal · 2023
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Dolfin: Diffusion layout transformers without autoencoder
Yilin Wang, Zeyuan Chen, Liangjun Zhong, Zheng Ding, Zhizhou Sha, and Zhuowen Tu · 2023
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Advances in medical image analysis with vision transformers: a comprehensive review
Reza Azad, Amirhossein Kazerouni, Moein Heidari, Ehsan Khodapanah Aghdam, Amirali Molaei, Yiwei Jia, Abin Jose, Rijo Roy, and Dorit Merhof · 2024
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Chenxin Li, Xinyu Liu, Wuyang Li, Cheng Wang, Hengyu Liu, Yifan Liu, Zhen Chen, and Yixuan Yuan · 2024
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On the expressive power of modern hopfield networks
Xiaoyu Li, Yuanpeng Li, Yingyu Liang, Zhenmei Shi, and Zhao Song · 2024
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Theoretical constraints on the expressive power of rope-based tensor attention transformers
Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song, and Mingda Wan · 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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Score-based generative diffusion models for social recommendations
Chengyi Liu, Jiahao Zhang, Shijie Wang, Wenqi Fan, and Qing Li · 2024
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Segment anything in medical images
Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, and Bo Wang · 2024
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A logic for expressing log-precision transformers
William Merrill and Ashish Sabharwal · 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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Is a picture worth a thousand words? delving into spatial reasoning for vision language models
Jiayu Wang, Yifei Ming, Zhenmei Shi, Vibhav Vineet, Xin Wang, Yixuan Li, and Neel Joshi · 2024
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Tokencompose: Text-to-image diffusion with token-level supervision
Zirui Wang, Zhizhou Sha, Zheng Ding, Yilin Wang, and Zhuowen Tu · 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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Raphael: Text-to-image generation via large mixture of diffusion paths
Zeyue Xue, Guanglu Song, Qiushan Guo, Boxiao Liu, Zhuofan Zong, Yu Liu, and Ping Luo · 2024
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Pixart- s i g m a sigma : Weak-to-strong training of diffusion transformer for 4k text-to-image generation
Junsong Chen, Chongjian Ge, Enze Xie, Yue Wu, Lewei Yao, Xiaozhe Ren, Zhongdao Wang, Ping Luo, Huchuan Lu, and Zhenguo Li · 2025
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Mambair: A simple baseline for image restoration with state-space model
Hang Guo, Jinmin Li, Tao Dai, Zhihao Ouyang, Xudong Ren, and Shu-Tao Xia · 2025
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Diffbir: Toward blind image restoration with generative diffusion prior
Xinqi Lin, Jingwen He, Ziyan Chen, Zhaoyang Lyu, Bo Dai, Fanghua Yu, Yu Qiao, Wanli Ouyang, and Chao Dong · 2025
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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, Zhihao Shu, Wei Niu, Pu Zhao, Yanzhi Wang, and Jiuxiang Gu · 2025
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Numerical pruning for efficient autoregressive models
Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Jing Liu, Ruiyi Zhang, Ryan A. Rossi, Hao Tan, Tong Yu, Xiang Chen, Yufan Zhou, Tong Sun, Pu Zhao, Yanzhi Wang, and Jiuxiang Gu · 2025
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