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Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation

arXiv 1905.05621 ↗First posted 14 May 2019cs.CLcited by 84

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Abstract (arXiv)

Disentangling the content and style in the latent space is prevalent in unpaired text style transfer. However, two major issues exist in most of the current neural models. 1) It is difficult to completely strip the style information from the semantics for a sentence. 2) The recurrent neural network (RNN) based encoder and decoder, mediated by the latent representation, cannot well deal with the issue of the long-term dependency, resulting in poor preservation of non-stylistic semantic content. In this paper, we propose the Style Transformer, which makes no assumption about the latent representation of source sentence and equips the power of attention mechanism in Transformer to achieve better style transfer and better content preservation.

Key facts. Cited by 84 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 May 2019.

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Citing papers per year: 2021: 29; 2022: 17; 2023: 20; 2024: 11; 2025: 6; 2026: 1.

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  1. 2021FUDGE: Controlled Text Generation With Future Discriminatorscited by 374
  2. 2022RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learningcited by 361
  3. 2022Diffusion Models already have a Semantic Latent Spacecited by 324
  4. 2023Pretraining Language Models with Human Preferencescited by 245
  5. 2021StyTr2: Image Style Transfer with Transformerscited by 186
  6. 2021Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfercited by 147
  7. 2021A Recipe For Arbitrary Text Style Transfer with Large Language Modelscited by 107
  8. 2021Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approachcited by 75
  9. 2021Mitigating Political Bias in Language Models Through Reinforced Calibrationcited by 73
  10. 2023PFNs4BO: In-Context Learning for Bayesian Optimizationcited by 70
  11. 2023Detecting and Grounding Multi-Modal Media Manipulation and Beyondcited by 55
  12. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 50
38 more
  1. 2022Prompt-and-Rerank: A Method for Zero-Shot and Few-Shot Arbitrary Textual Style Transfer with Small Language Modelscited by 49
  2. 2023ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfercited by 49
  3. 2021Generating Syntactically Controlled Paraphrases without Using Annotated Parallel Pairscited by 45
  4. 2022A Causal Lens for Controllable Text Generationcited by 45
  5. 2021MuseMorphose: Full-Song and Fine-Grained Piano Music Style Transfer with One Transformer VAEcited by 39
  6. 2023Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformationcited by 39
  7. 2021Civil Rephrases Of Toxic Texts With Self-Supervised Transformerscited by 32
  8. 2024StyleDistance: Stronger Content-Independent Style Embeddings with Synthetic Parallel Examplescited by 32
  9. 2023Learning Interpretable Style Embeddings via Prompting LLMscited by 29
  10. 2022Composable Text Controls in Latent Space with ODEscited by 28
  11. 2021Detect and Perturb: Neutral Rewriting of Biased and Sensitive Text via Gradient-based Decodingcited by 23
  12. 2021Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalizationcited by 20
  13. 2022Dance Style Transfer with Cross-modal Transformercited by 20
  14. 2023MedEval: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluationcited by 19
  15. 2021A Review of Text Style Transfer using Deep Learningcited by 18
  16. 2021Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generationcited by 17
  17. 2022Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalizationcited by 17
  18. 2023STEER: Unified Style Transfer with Expert Reinforcementcited by 14
  19. 2023A Call for Standardization and Validation of Text Style Transfer Evaluationcited by 13
  20. 2024Counterfactual Generation with Identifiability Guaranteescited by 13
  21. 2021Transductive Learning for Unsupervised Text Style Transfercited by 12
  22. 2022Non-Parallel Text Style Transfer with Self-Parallel Supervisioncited by 11
  23. 2023Stylized Data-to-Text Generation: A Case Study in the E-Commerce Domaincited by 11
  24. 2024Authorship Style Transfer with Policy Optimizationcited by 11
  25. 2021Generic resources are what you need: Style transfer tasks without task-specific parallel training datacited by 10
  26. 2021Transferable Persona-Grounded Dialogues via Grounded Minimal Editscited by 10
  27. 2024CAT-LLM: Style-enhanced Large Language Models with Text Style Definition for Chinese Article-style Transfercited by 10
  28. 2021Political Depolarization of News Articles Using Attribute-aware Word Embeddingscited by 9
  29. 2021Revisiting Contextual Toxicity Detection in Conversationscited by 8
  30. 2022StoryTrans: Non-Parallel Story Author-Style Transfer with Discourse Representations and Content Enhancingcited by 8
  31. 2021NAST: A Non-Autoregressive Generator with Word Alignment for Unsupervised Text Style Transfercited by 7
  32. 2022So Different Yet So Alike! Constrained Unsupervised Text Style Transfercited by 7
  33. 2023Balancing the Style-Content Trade-Off in Sentiment Transfer Using Polarity-Aware Denoisingcited by 7
  34. 2024Unsupervised Text Style Transfer via LLMs and Attention Masking with Multi-way Interactionscited by 7
  35. 2023Prefix-Tuning Based Unsupervised Text Style Transfercited by 6
  36. 2023VERVE: Template-based ReflectiVE Rewriting for MotiVational IntErviewingcited by 6
  37. 2021Self-Supervised Knowledge Assimilation for Expert-Layman Text Style Transfercited by 5
  38. 2021From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Surveycited by 5

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