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This paper presents the Text Encoding Diffusion Model (TEncDM), a novel approach to diffusion modeling that operates in the space of pre-trained language model encodings.
BERTScore: Evaluating Text Generation with BERT
Zhang, T.; Kishore, V.; Wu, F.; Weinberger, K. Q.; and Artzi, Y. 2020 · 1904
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RoBERTa: A Robustly Optimized BERT Pretraining Approach
Liu, Y.; Ott, M.; Goyal, N.; Du, J.; Joshi, M.; Chen, D.; Levy, O.; Lewis, M.; Zettlemoyer, L.; and Stoyanov, V. 2019 · 1907
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Rouge: A package for automatic evaluation of summaries
Lin, C.-Y. 2004 · 2004
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A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories
Mostafazadeh, N.; Chambers, N.; He, X.; Parikh, D.; Batra, D.; Vanderwende, L.; Kohli, P.; and Allen, J. 2016 · 2016
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Quora Question Pairs
Chen, Z.; Zhang, H.; Zhang, X.; and Zhao, L. 2017 · 2017
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Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization
Narayan, S.; Cohen, S. B.; and Lapata, M. 2018 · 2018
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
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Language Models are Unsupervised Multitask Learners
Radford, A.; Wu, J.; Child, R.; Luan, D.; Amodei, D.; and Sutskever, I. 2019 · 2019
Earlier work this paper cites.
Neural CRF Model for Sentence Alignment in Text Simplification
Jiang, C.; Maddela, M.; Lan, W.; Zhong, Y.; and Xu, W. 2020 · 2020
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BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
Lewis, M.; Liu, Y.; Goyal, N.; Ghazvininejad, M.; Mohamed, A.; Levy, O.; Stoyanov, V.; and Zettlemoyer, L. 2020 · 2020
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 2020
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Structured Denoising Diffusion Models in Discrete State-Spaces
Austin, J.; Johnson, D. D.; Ho, J.; Tarlow, D.; and van den Berg, R. 2021 · 2021
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Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
Hoogeboom, E.; Nielsen, D.; Jaini, P.; Forré, P.; and Welling, M. 2021 · 2021
Earlier work this paper cites.
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers
Pillutla, K.; Swayamdipta, S.; Zellers, R.; Thickstun, J.; Welleck, S.; Choi, Y.; and Harchaoui, Z. 2021 · 2021
Cited alongside, same era.
Score-Based Generative Modeling through Stochastic Differential Equations
Song, Y.; Sohl-Dickstein, J.; Kingma, D. P.; Kumar, A.; Ermon, S.; and Poole, B. 2021 · 2021
Cited alongside, same era.
Diffusion-LM Improves Controllable Text Generation
Li, X.; Thickstun, J.; Gulrajani, I.; Liang, P. S.; and Hashimoto, T. B. 2022 · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Rombach, R.; Blattmann, A.; Lorenz, D.; Esser, P.; and Ommer, B. 2022 · 2022
Cited alongside, same era.
Self-conditioned Embedding Diffusion for Text Generation
Strudel, R.; Tallec, C.; Altché, F.; Du, Y.; Ganin, Y.; Mensch, A.; Grathwohl, W.; Savinov, N.; Dieleman, S.; Sifre, L.; and Leblond, R. 2022 · 2022
Cited alongside, same era.
Latent Diffusion for Language Generation
Lovelace, J.; Kishore, V.; Wan, C.; Shekhtman, E.; and Weinberger, K. Q. 2023 · 2023
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On Distillation of Guided Diffusion Models
Meng, C.; Rombach, R.; Gao, R.; Kingma, D.; Ermon, S.; Ho, J.; and Salimans, T. 2023 · 2023
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OpenAI. 2023 · 2023
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SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
Podell, D.; English, Z.; Lacey, K.; Blattmann, A.; Dockhorn, T.; Müller, J.; Penna, J.; and Rombach, R. 2023 · 2023
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AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
Wu, T.; Fan, Z.; Liu, X.; Zheng, H.-T.; Gong, Y.; yelong shen; Jiao, J.; Li, J.; zhongyu wei; Guo, J.; Duan, N.; and Chen, W. 2023 · 2023
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A Contrastive Framework for Neural Text Generation
Su, Y.; Lan, T.; Wang, Y.; Yogatama, D.; Kong, L.; and Collier, N. 2022 · 2022
Cited alongside, same era.
Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
Blattmann, A.; Dockhorn, T.; Kulal, S.; Mendelevitch, D.; Kilian, M.; Lorenz, D.; Levi, Y.; English, Z.; Voleti, V.; Letts, A.; Jampani, V.; and Rombach, R. 2023 · 2023
Cited alongside, same era.
Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning
Chen, T.; Zhang, R.; and Hinton, G. 2023 · 2023
Cited alongside, same era.
DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models
Gong, S.; Li, M.; Feng, J.; Wu, Z.; and Kong, L. 2023 · 2023
Cited alongside, same era.
SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control
Han, X.; Kumar, S.; and Tsvetkov, Y. 2023 · 2023
Cited alongside, same era.
Simple diffusion: end-to-end diffusion for high resolution images
Hoogeboom, E.; Heek, J.; and Salimans, T. 2023 · 2023
Cited alongside, same era.
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Laurençon, H.; Saulnier, L.; Wang, T.; Akiki, C.; del Moral, A. V.; Scao, T. L.; Werra, L. V.; Mou, C.; Ponferrada, E. G.; Nguyen, H.; Frohberg, J.; Šaško, M.; Lhoest, Q.; McMillan-Major, A.; Dupont, G.; Biderman, S.; Rogers, A.; allal, L. B.; Toni, F. D.; Pistilli, G.; Nguyen, O.; Nikpoor, S.; Masoud, M.; Colombo, P.; de la Rosa, J.; Villegas, P.; Thrush, T.; Longpre, S.; Nagel, S.; Weber, L.; Muñoz, M.; Zhu, J.; Strien, D. V.; Alyafeai, Z.; Almubarak, K.; Vu, M. C.; Gonzalez-Dios, I.; Soroa, A.; Lo, K.; Dey, M.; Suarez, P. O.; Gokaslan, A.; Bose, S.; Adelani, D.; Phan, L.; Tran, H.; Yu, I.; Pai, S.; Chim, J.; Lepercq, V.; Ilic, S.; Mitchell, M.; Luccioni, S. A.; and Jernite, Y. 2023 · 2023
Cited alongside, same era.
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model
Zhang, Y.; Gu, J.; Wu, Z.; Zhai, S.; Susskind, J. M.; and Jaitly, N. 2023 · 2023
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Scaling instruction-finetuned language models
Chung, H. W.; Hou, L.; Longpre, S.; Zoph, B.; Tay, Y.; Fedus, W.; Li, Y.; Wang, X.; Dehghani, M.; Brahma, S.; et al. 2024 · 2024
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Dubey, A.; Jauhri, A.; Pandey, A.; Kadian, A.; Al-Dahle, A.; Letman, A.; Mathur, A.; Schelten, A.; Yang, A.; Fan, A.; and et al. 2024 · 2024
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Fast Timing-Conditioned Latent Audio Diffusion
Evans, Z.; Carr, C.; Taylor, J.; Hawley, S. H.; and Pons, J. 2024 · 2024
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Empowering Diffusion Models on the Embedding Space for Text Generation
Gao, Z.; Guo, J.; Tan, X.; Zhu, Y.; Zhang, F.; Bian, J.; and Xu, L. 2024 · 2024
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TESS: Text-to-Text Self-Conditioned Simplex Diffusion
Karimi Mahabadi, R.; Ivison, H.; Tae, J.; Henderson, J.; Beltagy, I.; Peters, M.; and Cohan, A. 2024 · 2024
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DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises
Ye, J.; Zheng, Z.; Bao, Y.; Qian, L.; and Wang, M. 2024 · 2024
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Text Diffusion Model with Encoder-Decoder Transformers for Sequence-to-Sequence Generation
Yuan, H.; Yuan, Z.; Tan, C.; Huang, F.; and Huang, S. 2024 · 2024
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