EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910979359506432 |
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| author | Lee, Che Hyun Kim, Heeseung Yeom, Jiheum Yoon, Sungroh |
| author_facet | Lee, Che Hyun Kim, Heeseung Yeom, Jiheum Yoon, Sungroh |
| contents | We propose EdiText, a controllable text editing method that modifies the reference text to desired attributes at various scales. We integrate an SDEdit-based editing technique that allows for broad adjustments in the degree of text editing. Additionally, we introduce a novel fine-level editing method based on self-conditioning, which allows subtle control of reference text. While being capable of editing on its own, this fine-grained method, integrated with the SDEdit approach, enables EdiText to make precise adjustments within the desired range. EdiText demonstrates its controllability to robustly adjust reference text at a broad range of levels across various tasks, including toxicity control and sentiment control. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_19765 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models Lee, Che Hyun Kim, Heeseung Yeom, Jiheum Yoon, Sungroh Computation and Language Machine Learning We propose EdiText, a controllable text editing method that modifies the reference text to desired attributes at various scales. We integrate an SDEdit-based editing technique that allows for broad adjustments in the degree of text editing. Additionally, we introduce a novel fine-level editing method based on self-conditioning, which allows subtle control of reference text. While being capable of editing on its own, this fine-grained method, integrated with the SDEdit approach, enables EdiText to make precise adjustments within the desired range. EdiText demonstrates its controllability to robustly adjust reference text at a broad range of levels across various tasks, including toxicity control and sentiment control. |
| title | EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models |
| topic | Computation and Language Machine Learning |
| url | https://arxiv.org/abs/2502.19765 |