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Diffusion-LM Improves Controllable Text Generation

Controlling the behavior of language models (LMs) without re-training is a major open problem in natural language generation. We develop a new non-autoregressive language model based on continuous diffusions that we call Diffusion-LM.

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Cite this as

Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto (2024). Dataset: Diffusion-LM Improves Controllable Text Generation. https://doi.org/10.57702/y6eyps02

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Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Defined In	https://doi.org/10.48550/arXiv.2205.14217
Author	Xiang Lisa Li
More Authors	John Thickstun Ishaan Gulrajani Percy Liang Tatsunori B. Hashimoto
Homepage	https://arxiv.org/abs/2204.06125