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We present Seed Diffusion Preview, a large-scale language model based on discrete-state diffusion, offering remarkably fast inference speed.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric A Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Non-autoregressive neural machine translation
Jiatao Gu, James Bradbury, Caiming Xiong, Victor OK Li, and Richard Socher · 2018
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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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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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Do you have the right scissors? tailoring pre-trained language models via Monte-Carlo methods
Ning Miao, Yuxuan Song, Hao Zhou, and Lei Li · 2020
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Monte carlo gradient estimation in machine learning
Shakir Mohamed, Mihaela Rosca, Michael Figurnov, and Andriy Mnih · 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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Glancing transformer for non-autoregressive neural machine translation
Lihua Qian, Hao Zhou, Yu Bao, Mingxuan Wang, Lin Qiu, Weinan Zhang, Yong Yu, and Lei Li · 2021
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Autoregressive diffusion models
Emiel Hoogeboom, Alexey A Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, and Tim Salimans · 2021
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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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Continuous diffusion for categorical data
Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, et al · 2022
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Directed acyclic transformer for non-autoregressive machine translation
Fei Huang, Hao Zhou, Yang Liu, Hang Li, and Minlie Huang · 2022
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Multi-lingual evaluation of code generation models
Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Uddin Ahmad, Shiqi Wang, Qing Sun, Mingyue Shang, et al · 2022
Cited alongside, same era.
Alex Graves, Rupesh Kumar Srivastava, Timothy Atkinson, and Faustino Gomez · 2023
Cited alongside, same era.
Discrete diffusion language modeling by estimating the ratios of the data distribution
Your absorbing discrete diffusion secretly models the conditional distributions of clean data
Jingyang Ou, Shen Nie, Kaiwen Xue, Fengqi Zhu, Jiacheng Sun, Zhenguo Li, and Chongxuan Li · 2024
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Diffusion glancing transformer for parallel sequence-to-sequence learning
Lihua Qian, Mingxuan Wang, Yang Liu, and Hao Zhou · 2024
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Acdit: Interpolating autoregressive conditional modeling and diffusion transformer
Jinyi Hu, Shengding Hu, Yuxuan Song, Yufei Huang, Mingxuan Wang, Hao Zhou, Zhiyuan Liu, Wei-Ying Ma, and Maosong Sun · 2024
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Bigcodebench: Benchmarking code generation with diverse function calls and complex instructions
Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, et al · 2024
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Aaron Lou, Chenlin Meng, and Stefano Ermon · 2023
Cited alongside, same era.
Can it edit? evaluating the ability of large language models to follow code editing instructions
Federico Cassano, Luisa Li, Akul Sethi, Noah Shinn, Abby Brennan-Jones, Jacob Ginesin, Edward Berman, George Chakhnashvili, Anton Lozhkov, Carolyn Jane Anderson, et al · 2023
Cited alongside, same era.
https://blog.google/technology/google-deepmind/gemini-diffusion/
Google DeepMind · 2024
Cited alongside, same era.
Alphafold protein structure database in 2024: providing structure coverage for over 214 million protein sequences
Mihaly Varadi, Damian Bertoni, Paulyna Magana, Urmila Paramval, Ivanna Pidruchna, Malarvizhi Radhakrishnan, Maxim Tsenkov, Sreenath Nair, Milot Mirdita, Jingi Yeo, et al · 2024
Cited alongside, same era.
Likelihood-based diffusion language models
Ishaan Gulrajani and Tatsunori B Hashimoto · 2024
Cited alongside, same era.
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
Cited alongside, same era.
Simplified and generalized masked diffusion for discrete data
Jiaxin Shi, Kehang Han, Zhe Wang, Arnaud Doucet, and Michalis K Titsias · 2024
Cited alongside, same era.
Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, and Ion Stoica · 2024
Later among the works it cites.
Naturalcodebench: Examining coding performance mismatch on humaneval and natural user prompts
Shudan Zhang, Hanlin Zhao, Xiao Liu, Qinkai Zheng, Zehan Qi, Xiaotao Gu, Xiaohan Zhang, Yuxiao Dong, and Jie Tang · 2024
Later among the works it cites.
Mercury: Ultra-fast language models based on diffusion
Samar Khanna, Siddhant Kharbanda, Shufan Li, Harshit Varma, Eric Wang, Sawyer Birnbaum, Ziyang Luo, Yanis Miraoui, Akash Palrecha, Stefano Ermon, et al · 2025
Closest in time.
Large language diffusion models
Shen Nie, Fengqi Zhu, Zebin You, Xiaolu Zhang, Jingyang Ou, Jun Hu, Jun Zhou, Yankai Lin, Ji-Rong Wen, and Chongxuan Li · 2025
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Seed-coder: Let the code model curate data for itself
Yuyu Zhang, Jing Su, Yifan Sun, Chenguang Xi, Xia Xiao, Shen Zheng, Anxiang Zhang, Kaibo Liu, Daoguang Zan, Tao Sun, et al · 2025
Closest in time.
Block diffusion: Interpolating between autoregressive and diffusion language models
Marianne Arriola, Aaron Gokaslan, Justin T Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, and Volodymyr Kuleshov · 2025
Closest in time.