Papers with Language rectified flow

1 papers
LanguageFlow: Advancing Diffusion Language Generation with Probabilistic Flows (2024.naacl-long)

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Challenge: Recent work has demonstrated success in controlling sentence attributes and structure based on diffusion language models.
Approach: They propose a language-rectified flow method that reformulates standard probabilistic flow models to learn ordinary differential equations to transport between the source and target distributions.
Outcome: The proposed method outperforms baselines on three fine-grained control tasks and multiple high-quality text editing tasks.

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