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The recent surge of generative AI has been fueled by the generative power of diffusion probabilistic models and the scalable capabilities of large language models.
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Diffwave: A versatile diffusion model for audio synthesis
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Glu variants improve transformer
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Training verifiers to solve math word problems
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Diffusion models beat gans on image synthesis
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Larger-scale transformers for multilingual masked language modeling
Naman Goyal, Jingfei Du, Myle Ott, Giri Anantharaman, and Alexis Conneau · 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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Chimera: efficiently training large-scale neural networks with bidirectional pipelines
Shigang Li and Torsten Hoefler · 2021
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Learning transferable visual models from natural language supervision
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Emergent abilities of large language models
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Seqdiffuseq: Text diffusion with encoder-decoder transformers
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Examining scaling and transfer of language model architectures for machine translation
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The reversal curse: Llms trained on" a is b" fail to learn" b is a"
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Specializing smaller language models towards multi-step reasoning
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Multitask prompted training enables zero-shot task generalization, 2021
Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Fevry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, and Alexander M. Rush · 2021
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Step-unrolled denoising autoencoders for text generation
Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, and Aaron van den Oord · 2021
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le · 2021
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Kushal Arora, Layla El Asri, Hareesh Bahuleyan, and Jackie Chi Kit Cheung · 2022
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Maskgit: Masked generative image transformer
Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T Freeman · 2022
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Palm: Scaling language modeling with pathways, 2022
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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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Diffusionbert: Improving generative masked language models with diffusion models
Zhengfu He, Tianxiang Sun, Kuanning Wang, Xuanjing Huang, and Xipeng Qiu · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
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The flan collection: Designing data and methods for effective instruction tuning
Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V Le, Barret Zoph, Jason Wei, et al · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Dinoiser: Diffused conditional sequence learning by manipulating noises
Jiasheng Ye, Zaixiang Zheng, Yu Bao, Lihua Qian, and Mingxuan Wang · 2023
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Speechgpt: Empowering large language models with intrinsic cross-modal conversational abilities
Dong Zhang, Shimin Li, Xin Zhang, Jun Zhan, Pengyu Wang, Yaqian Zhou, and Xipeng Qiu · 2023
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Lumiere: A space-time diffusion model for video generation
Omer Bar-Tal, Hila Chefer, Omer Tov, Charles Herrmann, Roni Paiss, Shiran Zada, Ariel Ephrat, Junhwa Hur, Yuanzhen Li, Tomer Michaeli, et al · 2024
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Scaling diffusion language models via adaptation from autoregressive models
Shansan Gong, Shivam Agarwal, Yizhe Zhang, Jiacheng Ye, Lin Zheng, Mukai Li, Chenxin An, Peilin Zhao, Wei Bi, Jiawei Han, et al · 2024
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2024
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Scaling up masked diffusion models on text
Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang, Qian Liu, Guangtao Zeng, Min Lin, and Chongxuan Li · 2024
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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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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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Predicting emergent capabilities by finetuning
Charlie Snell, Eric Wallace, Dan Klein, and Sergey Levine · 2024
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Beyond autoregression: Discrete diffusion for complex reasoning and planning
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Anygpt: Unified multimodal llm with discrete sequence modeling
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Discrete flow matching
Itai Gat, Tal Remez, Neta Shaul, Felix Kreuk, Ricky TQ Chen, Gabriel Synnaeve, Yossi Adi, and Yaron Lipman · 2025
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Large language diffusion models, 2025
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Towards system 2 reasoning in llms: Learning how to think with meta chain-of-though
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