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Discrete diffusion has achieved state-of-the-art performance, outperforming or approaching autoregressive models on standard benchmarks.
A general method for numerically simulating the stochastic time evolution of coupled chemical reactions
Daniel T Gillespie · 1976
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Exact stochastic simulation of coupled chemical reactions
Daniel T Gillespie · 1977
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Markov chains
James R Norris · 1998
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Large text compression benchmark, 2011
Matt Mahoney · 2011
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GANs trained by a two time-scale update rule converge to a local Nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Stochastic modelling for systems biology
Darren J Wilkinson · 2018
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Mask-predict: Parallel decoding of conditional masked language models
Marjan Ghazvininejad, Omer Levy, Yinhan Liu, and Luke Zettlemoyer · 2019
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 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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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 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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Structured denoising diffusion models in discrete state-spaces
Jacob Austin, Daniel D Johnson, Jonathan Ho, Daniel Tarlow, and Rianne Van Den Berg · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Björn Ommer · 2021
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Argmax flows and multinomial diffusion: Learning categorical distributions
Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, and Max Welling · 2021
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GPT-J-6B: A 6 billion parameter autoregressive language model, 2021
Ben Wang and Aran Komatsuzaki · 2021
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A continuous time framework for discrete denoising models
Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, and Arnaud Doucet · 2022
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Maskgit: Masked generative image transformer
Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T Freeman · 2022
Evolutionary-scale prediction of atomic-level protein structure with a language model
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Nikita Smetanin, Robert Verkuil, Ori Kabeli, Yaniv Shmueli, et al · 2023
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Flow matching for generative modeling
Yaron Lipman, Ricky TQ Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2023
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2023
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Scalable diffusion models with transformers, 2023
William Peebles and Saining Xie · 2023
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Score-based continuous-time discrete diffusion models
Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, and Hanjun Dai · 2023
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Restart sampling for improving generative processes
Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, and Tommi Jaakkola · 2023
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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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Step-unrolled denoising autoencoders for text generation
Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, and Aaron van den Oord · 2022
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Vector-quantized image modeling with improved vqgan
Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, and Yonghui Wu · 2022
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Protein generation with evolutionary diffusion: sequence is all you need
Sarah Alamdari, Nitya Thakkar, Rianne van den Berg, Alex X Lu, Nicolo Fusi, Ava P Amini, and Kevin K Yang · 2023
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Building normalizing flows with stochastic interpolants
Michael S Albergo and Eric Vanden-Eijnden · 2023
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Dirichlet diffusion score model for biological sequence generation
Pavel Avdeyev, Chenlai Shi, Yuhao Tan, Kseniia Dudnyk, and Jian Zhou · 2023
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A reparameterized discrete diffusion model for text generation
Lin Zheng, Jianbo Yuan, Lei Yu, and Lingpeng Kong · 2023
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Generative flows on discrete state-spaces: Enabling multimodal flows with applications to protein co-design
Andrew Campbell, Jason Yim, Regina Barzilay, Tom Rainforth, and Tommi Jaakkola · 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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Discrete diffusion language modeling by estimating the ratios of the data distribution
Aaron Lou, Chenlin Meng, and Stefano Ermon · 2024
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Simple and effective masked diffusion language models
Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T Chiu, Alexander Rush, and Volodymyr Kuleshov · 2024
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Simplified and generalized masked diffusion for discrete data
Jiaxin Shi, Kehang Han, Zhe Wang, Arnaud Doucet, and Michalis K Titsias · 2024
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Roformer: Enhanced transformer with rotary position embedding
Jianlin Su, Murtadha Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu · 2024
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