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Masked diffusion language models (MDMs) have recently gained traction as a viable generative framework for natural language.
Bleu: a method for automatic evaluation of machine translation
K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu · 2002
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ROUGE: A package for automatic evaluation of summaries
C.-Y. Lin · 2004
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
S. Banerjee and A. Lavie · 2005
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Optimizing statistical machine translation for text simplification
W. Xu, C. Napoles, E. Pavlick, Q. Chen, and C. Callison-Burch · 2016
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Evaluating prose style transfer with the bible
K. Carlson, A. B. Riddell, and D. N. Rockmore · 2017
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Sentence simplification with deep reinforcement learning
X. Zhang and M. Lapata · 2017
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Multi-task neural models for translating between styles within and across languages
X. Niu, S. Rao, and M. Carpuat · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2019
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Decoupled weight decay regularization
I. Loshchilov and F. Hutter · 2019
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Language models are few-shot learners
T. B. Brown and et al · 2020
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Complementary auxiliary classifiers for label-conditional text generation
Y. Li, C. Li, Y. Zhang, X. Li, G. Zheng, L. Carin, and J. Gao · 2020
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Bertscore: Evaluating text generation with BERT
T. Zhang, V. Kishore, F. Wu, K. Q. Weinberger, and Y. Artzi · 2020
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Structured denoising diffusion models in discrete state-spaces
J. Austin, D. D. Johnson, J. Ho, D. Tarlow, and R. van den Berg · 2021
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Diffusion models beat gans on image synthesis
P. Dhariwal and A. Nichol · 2021
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Classifier-free diffusion guidance
J. Ho and T. Salimans · 2021
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Argmax flows and multinomial diffusion: Learning categorical distributions
E. Hoogeboom, D. Nielsen, P. Jaini, P. Forr’e, and M. Welling · 2021
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Denoising diffusion implicit models
J. Song, C. Meng, and S. Ermon · 2021
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Maskgit: Masked generative image transformer
H. Chang, H. Zhang, L. Jiang, C. Liu, and W. T. Freeman · 2022
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Deep learning for text style transfer: A survey
D. Jin, Z. Jin, Z. Hu, O. Vechtomova, and R. Mihalcea · 2022
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A. Dubey and et al · 2024
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Derivative-free guidance in continuous and discrete diffusion models with soft value-based decoding
X. Li, Y. Zhao, C. Wang, G. Scalia, G. Eraslan, S. Nair, T. Biancalani, A. Regev, S. Levine, and M. Uehara · 2024
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Discrete diffusion modeling by estimating the ratios of the data distribution
A. Lou, C. Meng, and S. Ermon · 2024
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Unlocking guidance for discrete state-space diffusion and flow models
H. Nisonoff, J. Xiong, S. Allenspach, and J. Listgarten · 2024
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Simple and effective masked diffusion language models
S. S. Sahoo, M. Arriola, Y. Schiff, A. Gokaslan, E. Marroquin, J. T. Chiu, A. Rush, and V. Kuleshov · 2024
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Diffuseq: Sequence to sequence text generation with diffusion models
S. Gong, M. Li, J. Feng, Z. Wu, and L. Kong · 2023
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Text generation with diffusion language models: a pre-training approach with continuous paragraph denoise
Z. Lin, Y. Gong, Y. Shen, T. Wu, Z. Fan, C. Lin, N. Duan, and W. Chen · 2023
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Fine-grained text style transfer with diffusion-based language models
Y. Lyu, T. Luo, J. Shi, T. Hollon, and H. Lee · 2023
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LENS: A learnable evaluation metric for text simplification
M. Maddela, Y. Dou, D. Heineman, and W. Xu · 2023
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SlimPajama: A 627B token cleaned and deduplicated version of RedPajama, 2023
D. Soboleva, F. Al-Khateeb, R. Myers, J. R. Steeves, J. Hestness, and N. Dey · 2023
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Diffusion posterior sampling for linear inverse problem solving: A filtering perspective
Z. Dou and Y. Song · 2024
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Simplified and generalized masked diffusion for discrete data
J. Shi, K. Han, Z. Wang, A. Doucet, and M. Titsias · 2024
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A. Yang and et al · 2024
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TFG: Unified training-free guidance for diffusion models
H. Ye and et al · 2024
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Smollm2: When smol goes big - data-centric training of a small language model
L. B. Allal and et al · 2025
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Debiasing guidance for discrete diffusion with sequential monte carlo
C. K. Lee, P. Jeha, J. Frellsen, P. Lio, M. S. Albergo, and F. Vargas · 2025
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Inference-time scaling for diffusion models beyond scaling denoising steps
N. Ma, S. Tong, H. Jia, H. Hu, Y. Su, M. Zhang, X. Yang, Y. Li, T. S. Jaakkola, X. Jia, and S. Xie · 2025
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Simple guidance mechanisms for discrete diffusion models
Y. Schiff, S. S. Sahoo, H. Phung, G. Wang, S. Boshar, H. Dalla-torre, B. P. de Almeida, A. M. Rush, T. PIERROT, and V. Kuleshov · 2025
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