Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization (2021.acl-long)
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| Challenge: | Text style transfer aims to alter the style of a sentence while preserving its content. |
| Approach: | They propose to remove style information at token level and fuse it to style representations using conditional layer normalization. |
| Outcome: | The proposed model outperforms the state-of-the-art models in terms of content preservation and fluency. |
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| Challenge: | Existing methods for short TST are difficult to implement and can cause content degradation. |
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Style versus Content: A distinction without a (learnable) difference? (2020.coling-main)
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| Challenge: | Textual style transfer assumes that it is possible to separate style from content . however, style transfer can provide insight into language more generally . |
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TextSETTR: Few-Shot Text Style Extraction and Tunable Targeted Restyling (2021.acl-long)
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| Challenge: | Existing methods for text style transfer require style-labeled training data, but use only labeled data at inference time. |
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Text Style Transfer for Bias Mitigation using Masked Language Modeling (2022.naacl-srw)
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| Challenge: | Various research findings have concluded that biased textual data has significant effects on target demographic groups. |
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How Positive Are You: Text Style Transfer using Adaptive Style Embedding (2020.coling-main)
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| Challenge: | Existing approaches for unsupervised text style transfer are disentanglement between content and style. |
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| Challenge: | Disentangling the content and style in the latent space is prevalent in text style transfer . recurrent neural networks (RNN) based encoder and decoder cannot deal with the long-term dependency . |
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StyleFlow: Disentangle Latent Representations via Normalizing Flow for Unsupervised Text Style Transfer (2024.lrec-main)
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| Challenge: | Existing methods to separate content from style but some words contain both content and style information. |
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Reference-guided Style-Consistent Content Transfer (2024.lrec-main)
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| Challenge: | Text style transfer involves changing the style of a text while preserving its original style. |
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Text Style Transferring via Adversarial Masking and Styled Filling (2022.emnlp-main)
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| Challenge: | Existing models for text style transfer suffer from two challenges: the word masking procedure may mistakenly remove unexpected words and the selected words in the word filling procedure lack diversity and semantic consistency. |
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Style Transfer Through Back-Translation (P18-1)
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| Challenge: | a new method for automatic style transfer is proposed to preserve the meaning of the text while reducing stylistic properties. |
| Approach: | They propose a method for automatic style transfer that uses latent representations of the input sentence to preserve meaning while reducing stylistic properties. |
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