mlsanityData to 7 Oct 2026

Shakespearizing Modern Language Using Copy-Enriched Sequence-to-Sequence Models

arXiv 1707.01161 ↗First posted 4 Jul 2017cs.CLcited by 57

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Abstract (arXiv)

Variations in writing styles are commonly used to adapt the content to a specific context, audience, or purpose. However, applying stylistic variations is still by and large a manual process, and there have been little efforts towards automating it. In this paper we explore automated methods to transform text from modern English to Shakespearean English using an end to end trainable neural model with pointers to enable copy action. To tackle limited amount of parallel data, we pre-train embeddings of words by leveraging external dictionaries mapping Shakespearean words to modern English words as well as additional text. Our methods are able to get a BLEU score of 31+, an improvement of ~6 points above the strongest baseline. We publicly release our code to foster further research in this area.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jul 2017.

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Citing papers per year: 2021: 16; 2022: 16; 2023: 7; 2024: 11; 2025: 4; 2026: 3.

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  1. 2022RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learningcited by 361
  2. 2022Challenges and Strategies in Cross-Cultural NLPcited by 216
  3. 2021ExT5: Towards Extreme Multi-Task Scaling for Transfer Learningcited by 161
  4. 2024Style Vectors for Steering Generative Large Language Modelcited by 56
  5. 2022Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Expertscited by 36
  6. 2021StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfercited by 34
  7. 2022Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterancescited by 32
  8. 2022Inducing Positive Perspectives with Text Reframingcited by 31
  9. 2023TrojLLM: A Black-box Trojan Prompt Attack on Large Language Modelscited by 29
  10. 2023Don't lose the message while paraphrasing: A study on content preserving style transfercited by 25
  11. 2022APPDIA: A Discourse-aware Transformer-based Style Transfer Model for Offensive Social Media Conversationscited by 23
  12. 2021Few-shot Controllable Style Transfer for Low-Resource Multilingual Settingscited by 20
38 more
  1. 2022Why is constrained neural language generation particularly challenging?cited by 19
  2. 2021A Review of Text Style Transfer using Deep Learningcited by 18
  3. 2022FRMT: A Benchmark for Few-Shot Region-Aware Machine Translationcited by 18
  4. 2023A Systematic Study of Knowledge Distillation for Natural Language Generation with Pseudo-Target Trainingcited by 16
  5. 2024MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimizationcited by 16
  6. 2021Improving Formality Style Transfer with Context-Aware Rule Injectioncited by 13
  7. 2021A Survey of Natural Language Generationcited by 13
  8. 2022Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priorscited by 13
  9. 2024Distilling Text Style Transfer With Self-Explanation From LLMscited by 12
  10. 2024Text Detoxification as Style Transfer in English and Hindicited by 11
  11. 2025Measuring and Guiding Monosemanticitycited by 10
  12. 2023Learning to Generate Text in Arbitrary Writing Stylescited by 9
  13. 2024Multilingual Text Style Transfer: Datasets & Models for Indian Languagescited by 9
  14. 2021Metrical Tagging in the Wild: Building and Annotating Poetry Corpora with Rhythmic Featurescited by 8
  15. 2021NAST: A Non-Autoregressive Generator with Word Alignment for Unsupervised Text Style Transfercited by 7
  16. 2021Idiomatic Expression Paraphrasing without Strong Supervisioncited by 7
  17. 2022BERT in Plutarch's Shadowscited by 6
  18. 2024Using Prompts to Guide Large Language Models in Imitating a Real Person's Language Stylecited by 6
  19. 2024SCAR: Sparse Conditioned Autoencoders for Concept Detection and Steering in LLMscited by 6
  20. 2025When Style Breaks Safety: Defending LLMs Against Superficial Style Alignmentcited by 6
  21. 2021DRAG: Director-Generator Language Modelling Framework for Non-Parallel Author Stylized Rewritingcited by 5
  22. 2021StyleKQC: A Style-Variant Paraphrase Corpus for Korean Questions and Commandscited by 5
  23. 2021From Solving a Problem Boldly to Cutting the Gordian Knot: Idiomatic Text Generationcited by 5
  24. 2021From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Surveycited by 5
  25. 2023Audience-Centric Natural Language Generation via Style Infusioncited by 5
  26. 2024Text Style Transfer: An Introductory Overviewcited by 5
  27. 2025Steering Large Language Models with Register Analysis for Arbitrary Style Transfercited by 5
  28. 2022Low Resource Style Transfer via Domain Adaptive Meta Learningcited by 4
  29. 2022Exploiting Social Media Content for Self-Supervised Style Transfercited by 2
  30. 2022Style Transfer as Data Augmentation: A Case Study on Named Entity Recognitioncited by 2
  31. 2023Balancing Effect of Training Dataset Distribution of Multiple Styles for Multi-Style Text Transfercited by 2
  32. 2023Specializing Small Language Models towards Complex Style Transfer via Latent Attribute Pre-Trainingcited by 2
  33. 2025Graph Inverse Style Transfer for Counterfactual Explainabilitycited by 2
  34. 2021Changing the Narrative Perspective: From Deictic to Anaphoric Point of Viewcited by 1
  35. 2021Contextualizing Variation in Text Style Transfer Datasetscited by 1
  36. 2022Extending the Vocabulary of Fictional Languages using Neural Networkscited by 1
  37. 2022Studying the role of named entities for content preservation in text style transfercited by 1
  38. 2022Conciseness: An Overlooked Language Taskcited by 1

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