{"id":13650277,"url":"https://github.com/fuzhenxin/Style-Transfer-in-Text","last_synced_at":"2025-04-22T18:31:15.458Z","repository":{"id":31307575,"uuid":"123754708","full_name":"fuzhenxin/Style-Transfer-in-Text","owner":"fuzhenxin","description":"Paper List for Style Transfer in Text","archived":false,"fork":false,"pushed_at":"2023-03-16T03:19:15.000Z","size":150,"stargazers_count":1609,"open_issues_count":1,"forks_count":194,"subscribers_count":72,"default_branch":"master","last_synced_at":"2024-10-15T09:24:16.982Z","etag":null,"topics":["natural-language-processing","paper","style-transfer","survey"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/fuzhenxin.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2018-03-04T03:52:06.000Z","updated_at":"2024-09-22T05:01:30.000Z","dependencies_parsed_at":"2024-01-14T12:17:32.756Z","dependency_job_id":"9d7fa860-2c43-4a08-8669-e7bbd8d348dd","html_url":"https://github.com/fuzhenxin/Style-Transfer-in-Text","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fuzhenxin%2FStyle-Transfer-in-Text","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fuzhenxin%2FStyle-Transfer-in-Text/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fuzhenxin%2FStyle-Transfer-in-Text/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fuzhenxin%2FStyle-Transfer-in-Text/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fuzhenxin","download_url":"https://codeload.github.com/fuzhenxin/Style-Transfer-in-Text/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":223903078,"owners_count":17222485,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["natural-language-processing","paper","style-transfer","survey"],"created_at":"2024-08-02T02:00:35.506Z","updated_at":"2024-11-10T01:30:41.987Z","avatar_url":"https://github.com/fuzhenxin.png","language":null,"funding_links":[],"categories":["Natural Language Processing","NLP","Others"],"sub_categories":[],"readme":"# A Paper List for Style Transfer in Text\nThis is a paper list for style transfer in text. It also contains some related research areas, including controlled text generation.\n\n**Keyword:** *Style Transfer, Unsupervised, Natural Language Processing*\n\n# Paper List\n\n## Review\n- Deep Learning for Text Style Transfer: A Survey, arXiv, 2020, [[paper]](https://arxiv.org/pdf/2011.00416.pdf)\n- Text Style Transfer: A Review and Experiment Evaluation, arXiv, 2020, [[paper]](https://arxiv.org/pdf/2010.12742.pdf)\n- A Review of Text Style Transfer using Deep Learning, TAI, 2021, [[paper]](https://arxiv.org/abs/2109.15144)\n\n## Dataset\n- Dear Sir or Madam, May I introduce the YAFC Corpus: Corpus, Benchmarks and Metrics for Formality Style Transfer, NAACL-HLT 2018, [[paper]](https://arxiv.org/pdf/1803.06535)\n- A Dataset for Low-Resource Stylized Sequence-to-Sequence Generation, AAAI, 2020, [[paper]](https://www.msra.cn/wp-content/uploads/2020/01/A-Dataset-for-Low-Resource-Stylized-Sequence-to-Sequence-Generation.pdf), [[code]](https://github.com/MarkWuNLP/Data4StylizedS2S)\n- APPDIA: A Discourse-aware Transformer-based Style Transfer Model for Offensive Social Media Conversations, COLING 2022, [[paper]](https://aclanthology.org/2022.coling-1.530.pdf)\n- ParaDetox: Detoxification with Parallel Data, ACL 2022, [[paper]](https://aclanthology.org/2022.acl-long.469.pdf)\n\n## Supervised (Parallel Data)\n- Shakespearizing Modern Language Using Copy-Enriched Sequence to Sequence Models, EMNLP-2017 Workshop, [[paper]](https://arxiv.org/pdf/1707.01161)[[code]](https://github.com/harsh19/Shakespearizing-Modern-English)\n- Evaluating prose style transfer with the Bible, 2018, [[paper]](https://arxiv.org/pdf/1711.04731)\n- Harnessing Pre-Trained Neural Networks with Rules for Formality Style Transfer, EMNLP-2019, [[paper]](https://www.aclweb.org/anthology/D19-1365/), [[code]](https://github.com/jimth001/formality_emnlp19)\n- Automatically Neutralizing Subjective Bias in Text, AAAI, 2020, [[paper]](https://nlp.stanford.edu/pubs/pryzant2020bias.pdf)\n- Formality Style Transfer with Shared Latent Space, COLING 2020, [[paper]](https://www.aclweb.org/anthology/2020.coling-main.203.pdf)\n- Smells like Teen Spirit:An Exploration of Sensorial Style in Literary Genres, COLING 2022, [[paper]](https://aclanthology.org/2022.coling-1.6.pdf)\n- ParaDetox: Detoxification with Parallel Data, ACL 2022, [[paper]](https://aclanthology.org/2022.acl-long.469.pdf)\n\n## Unsupervised (Non-parallel Data)\n- Sequence to Better Sequence: Continuous Revision of Combinatorial Structures, ICML-2017, [[paper]](http://proceedings.mlr.press/v70/mueller17a.html), [[code]](https://bitbucket.org/jwmueller/sequence-to-better-sequence/)\n- Toward Controlled Generation of Text, ICML-2017, [[paper]](https://arxiv.org/pdf/1703.00955), [[official code]](https://github.com/asyml/texar/tree/master/examples/text_style_transfer), [[unofficial code]](https://github.com/GBLin5566/toward-controlled-generation-of-text-pytorch)\n- Style Transfer from Non-Parallel Text by Cross-Alignment, NIPS-2017, [[paper]](https://papers.nips.cc/paper/7259-style-transfer-from-non-parallel-text-by-cross-alignment.pdf), [[code]](https://github.com/shentianxiao/language-style-transfer)\n- Adversarially Regularized Autoencoders, ICML-2018, [[paper]](https://arxiv.org/pdf/1706.04223), [[code]](https://github.com/jakezhaojb/ARAE)\n- Zero-Shot Style Transfer in Text Using Recurrent Neural Networks, Arxiv-2017, [[paper]](https://arxiv.org/pdf/1711.04731v1), [[code]](https://github.com/keithecarlson/Zero-Shot-Style-Transfer)\n- Style Transfer in Text: Exploration and Evaluation, AAAI-2018, [[paper]](https://arxiv.org/pdf/1711.06861), [[code]](https://github.com/fuzhenxin/text_style_transfer)\n- Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer, NAACL-2018, [[paper]](https://arxiv.org/pdf/1804.06437), [[code]](https://worksheets.codalab.org/worksheets/0xe3eb416773ed4883bb737662b31b4948/)\n- SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation, NAACL-2018, [[paper]](https://arxiv.org/pdf/1804.04093)\n- Sentiment Transfer using Seq2Seq Adversarial Autoencoders, project for CSYE7245 Northeastern University, [[paper]](https://arxiv.org/pdf/1804.04003)\n- Style Transfer Through Back-Translation, ACL-2018, [[paper]](https://arxiv.org/pdf/1804.09000), [[code]](https://github.com/shrimai/Style-Transfer-Through-Back-Translation)\n- Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach, ACL-2018, [[paper]](https://arxiv.org/pdf/1805.05181), [[code]](https://github.com/lancopku/unpaired-sentiment-translation)\n- Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer, ACL-2018, [[paper]](https://arxiv.org/pdf/1805.07685)\n- Unsupervised Text Style Transfer using Language Models as Discriminators, NIPS-2018, [[paper]](https://arxiv.org/pdf/1805.11749)\n- Disentangled Representation Learning for Non-Parallel Text Style Transfer, ACL-2019, [[paper]](https://arxiv.org/pdf/1808.04339), [[code]](https://github.com/vineetjohn/linguistic-style-transfer)\n- Language Style Transfer from Sentences with Arbitrary Unknown Styles, Arxiv, [[paper]](https://arxiv.org/pdf/1808.04071)\n- Style Transfer as Unsupervised Machine Translation, Arxiv, [[paper]](https://arxiv.org/pdf/1808.07894)\n- Learning Sentiment Memories for Sentiment Modification without Parallel Data, EMNLP-2018, [[paper]](https://arxiv.org/pdf/1808.07311), [[code]](https://github.com/lancopku/SMAE)\n- Style Transfer Through Multilingual and Feedback-Based Back-Translation, Arxiv, 2018, [[paper]](https://arxiv.org/pdf/1809.06284)\n- Structured Content Preservation for Unsupervised Text Style Transfer, OpenReview, 2018, [[paper]](https://openreview.net/forum?id=S1lCbhAqKX)\n- Unsupervised Controllable Text Formalization, AAAI, 2019, [[paper]](https://arxiv.org/pdf/1809.04556), [[code]](https://github.com/parajain/uctf)\n- Large-scale Hierarchical Alignment for Data-driven Text Rewriting, RANLP, 2019, [[paper]](https://arxiv.org/pdf/1810.08237)\n- Learning Criteria and Evaluation Metrics for Textual Transfer between Non-Parallel Corpora, Arxiv, 2018, [[paper]](https://arxiv.org/pdf/1810.11878)\n- Content preserving text generation with attribute controls, NIPS, 2018, [[paper]](https://arxiv.org/pdf/1811.01135)\n- QuaSE: Sequence Editing under Quantifiable Guidance, EMNLP, 2018, [[paper]](http://aclweb.org/anthology/D18-1420)\n- Adversarial Text Generation via Feature-Mover's Distance, NeurIPS, 2018, [[paper]](https://arxiv.org/pdf/1809.06297), [[unofficial code]](https://github.com/knok/chainer-fm-gan)\n- Towards Controlled Transformation of Sentiment in Sentences, ICAART, 2019, [[paper]](https://arxiv.org/pdf/1901.11467)\n- Formality Style Transfer with Hybrid Textual Annotations, Arxiv, 2019, [[paper]](https://arxiv.org/pdf/1903.06353)\n- Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus, NAACL-2019, 2019, [[paper]](https://arxiv.org/pdf/1903.10671)\n- Grammatical Error Correction and Style Transfer via Zero-shot Monolingual Translation, Arxiv, 2019, [[paper]](https://arxiv.org/pdf/1903.11283)\n- Multiple-Attribute Text Style Transfer (Rewriting), ICLR, 2019, [[paper]](https://openreview.net/forum?id=H1g2NhC5KQ)\n- Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation, ACL, 2019, [[paper]](https://arxiv.org/pdf/1905.05621)\n- A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer, IJCAI, 2019, [[paper]](https://arxiv.org/pdf/1905.10060), [[code]](https://github.com/luofuli/DualLanST)\n- On Variational Learning of Controllable Representations for Text without Supervision, ICML, 2020, [[paper]](http://proceedings.mlr.press/v119/xu20a/xu20a.pdf)\n- Revision in Continuous Space: Fine-Grained Control of Text Style Transfer, AAAI, 2020, [[paper]](https://arxiv.org/pdf/1905.12304)\n- Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation, NIPS, 2019, [[paper]](https://arxiv.org/pdf/1905.12926), [[code]](https://github.com/nrgeup/controllable-text-attribute-transfer)\n- Disentangled Representation Learning for Non-Parallel Text Style Transfer, ACL, 2019, [[paper]](https://www.aclweb.org/anthology/P19-1041), [[code]](https://github.com/vineetjohn/linguistic-style-transfer)\n- A Hierarchical Reinforced Sequence Operation Method for Unsupervised Text Style Transfer, ACL, 2019, [[paper]](https://www.aclweb.org/anthology/P19-1482), [[code]](https://github.com/ChenWu98/Point-Then-Operate)\n- Unsupervised Text Attribute Transfer via Iterative Matching and Translation, EMNLP, 2019, [[paper]](https://arxiv.org/pdf/1901.11333)\n- Mask and Infill: Applying Masked Language Model to Sentiment Transfer, IJCAI, 2019, [[paper]](https://arxiv.org/pdf/1908.08039)\n- Transforming Delete, Retrieve, Generate Approach for Controlled Text Style Transfer, EMNLP, 2019, [[paper]](https://arxiv.org/pdf/1908.09368), [[code]](https://github.com/agaralabs/transformer-drg-style-transfer)\n- Domain Adaptive Text Style Transfer, EMNLP, 2019, [[paper]](https://arxiv.org/pdf/1908.09395), [[code]](https://github.com/cookielee77/DAST)\n- Style Transfer for Texts: Retrain, Report Errors, Compare with Rewrites, EMNLP, 2019, [[paper]](https://arxiv.org/pdf/1908.06809.pdf), [[code]](https://github.com/VAShibaev/text_style_transfer)\n- Decomposing Textual Information For Style Transfer, WNGT, 2019, [[paper]](https://arxiv.org/pdf/1909.12928)\n- Zero-Shot Fine-Grained Style Transfer: Leveraging Distributed Continuous Style Representations to Transfer To Unseen Styles, Arxiv, 2019, [[paper]](https://arxiv.org/pdf/1911.03914)\n- A Probabilistic Formulation of Unsupervised Text Style Transfer, ICLR, 2020, [[paper]](https://openreview.net/forum?id=HJlA0C4tPS), [[code]](https://github.com/cindyxinyiwang/deep-latent-sequence-model)\n- Generating sentences from disentangled syntactic and semantic spaces, ACL, 2019, [[paper]](https://www.aclweb.org/anthology/P19-1602/), [[code]](https://github.com/baoy-nlp/DSS-VAE)\n- SentiInc: Incorporating Sentiment Information into Sentiment Transfer Without Parallel Data, ECIR, 2020, [[paper]](https://link.springer.com/content/pdf/10.1007%2F978-3-030-45442-5_39.pdf)\n- Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen, ACL, 2020, [[paper]](https://arxiv.org/pdf/2005.00701.pdf)\n- Contextual Text Style Transfer, Arxiv, 2020, [[paper]](https://arxiv.org/pdf/2005.00136.pdf)\n- Exploring Contextual Word-level Style Relevance for Unsupervised Style Transfer, ACL, 2020, [[paper]](https://arxiv.org/pdf/2005.02049.pdf)\n- ST$^2$: Small-data Text Style Transfer via Multi-task Meta-Learning, Arxiv, 2020, [[paper]](https://arxiv.org/pdf/2004.11742)\n- Reinforced Rewards Framework for Text Style Transfer, ECIR, 2020, [[paper]](https://arxiv.org/pdf/2005.05256)\n- Challenges in Emotion Style Transfer: An Exploration with a Lexical Substitution Pipeline, SocialNLP, ACL, 2020, [[paper]](https://arxiv.org/pdf/2005.07617.pdf)\n- Stable Style Transformer: Delete and Generate Approach with Encoder-Decoder for Text Style Transfer, Arxiv, 2020, [[paper]](https://arxiv.org/pdf/2005.12086.pdf)\n- Unsupervised Automatic Text Style Transfer Using LSTM, NLPCC, 2017, [[paper]](http://tcci.ccf.org.cn/conference/2017/papers/1135.pdf)\n- Text Style Transfer via Learning Style Instance Supported Latent Space, IJCAI, 2020, [[paper]](https://www.ijcai.org/Proceedings/2020/0526.pdf)\n- Learning to Generate Multiple Style Transfer Outputs for an Input Sentence, Arxiv, 2020, [[paper]](https://arxiv.org/pdf/2002.06525)\n- Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders, ACL, 2020, [[paper]](https://arxiv.org/pdf/1911.03882.pdf)\n- Unsupervised Text Style Transfer with Padded Masked Language Models, EMNLP, 2020, [[paper]](https://arxiv.org/pdf/2010.01054.pdf)\n- Reformulating Unsupervised Style Transfer as Paraphrase Generation, EMNLP 2020, [[paper]](https://arxiv.org/pdf/2010.05700.pdf)\n- Plug and Play Autoencoders for Conditional Text Generation, EMNLP 2020 [[paper]](https://arxiv.org/pdf/2010.02983.pdf)\n- DGST: a Dual-Generator Network for Text Style Transfer, EMNLP 2020, [[paper]](https://arxiv.org/pdf/2010.14557.pdf)\n- How Positive Are You: Text Style Transfer Using Adaptive Style Embedding, EMNLP 2020, [[paper]](https://www.aclweb.org/anthology/2020.coling-main.191.pdf)\n- Unsupervised Text Generation by Learning from Search, NeurIPS 2020, [[paper]](https://papers.nips.cc/paper/2020/file/7a677bb4477ae2dd371add568dd19e23-Paper.pdf)\n- Cycle-Consistent Adversarial Autoencoders for Unsupervised Text Style Transfer, COLING 2020, [[paper]](https://arxiv.org/pdf/2010.00735.pdf)\n- TextSETTR: Label-Free Text Style Extraction and Tunable Targeted Restyling, Arxiv, 2020, [[paper]](https://arxiv.org/pdf/2010.03802.pdf)\n- Non-parallel text style transfer with domain adaptation and an attention model, Applied Intelligence, 2021, [[paper]](https://link.springer.com/article/10.1007/s10489-020-02077-5), [[code]](https://github.com/mingxuan007/text-style-transfer-with-adversarial-network-and-domain-adaptation)\n- Exploring Non-Autoregressive Text Style Transfer, EMNLP, 2021, [[paper]](https://aclanthology.org/2021.emnlp-main.730.pdf)\n- Generic resources are what you need: Style transfer tasks without task-specific parallel training data, EMNLP, 2021, [[paper]](https://arxiv.org/pdf/2109.04543.pdf)\n- Style Pooling: Automatic Text Style Obfuscation for Improved Classification Fairness, EMNLP, 2021, [[paper]](https://aclanthology.org/2021.emnlp-main.152.pdf)\n- Transductive Learning for Unsupervised Text Style Transfer, EMNLP, 2021, [[paper]](https://arxiv.org/pdf/2109.07812.pdf)\n- Collaborative Learning of Bidirectional Decoders for Unsupervised Text Style Transfer, EMNLP, 2021, [[paper]](https://aclanthology.org/2021.emnlp-main.729.pdf)\n- On Learning Text Style Transfer with Direct Rewards, NAACL, 2021, [[paper]](https://arxiv.org/pdf/2010.12771.pdf)\n- STYLEPTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer, NAACL, 2021, [[paper]](https://arxiv.org/pdf/2104.05196.pdf),[[code]](https://github.com/lvyiwei1/StylePTB/)\n- Multi-Style Transfer with Discriminative Feedback on Disjoint Corpus, NAACL, 2021, [[paper]](https://arxiv.org/pdf/2010.11578.pdf)\n- Civil Rephrases Of Toxic Texts With Self-Supervised Transformers, EACL, 2021, [[paper]](https://arxiv.org/pdf/2102.05456.pdf), [[code]](https://github.com/LeoLaugier/conditional-auto-encoder-text-to-text-transfer-transformer)\n- Efficient Reinforcement Learning for Unsupervised Controlled Text Generation, Arxiv, 2022, [[paper]](https://arxiv.org/pdf/2204.07696.pdf)\n- So Different Yet So Alike! Constrained Unsupervised Text Style Transfer, ACL, 2022, [[paper]](https://aclanthology.org/2022.acl-long.32.pdf), [[code]](https://github.com/abhinavkashyap/dct)\n\n## Semi-supervised\n- Semi-supervised Text Style Transfer: Cross Projection in Latent Space, EMNLP, 2019, [[paper]](https://arxiv.org/pdf/1909.11493)\n- Parallel Data Augmentation for Formality Style Transfer, ACL, 2020, [[paper]](https://arxiv.org/pdf/2005.07522.pdf)\n- Semi-Supervised Formality Style Transfer with Consistency Training, ACL, 2022, [[paper]](https://aclanthology.org/2022.acl-long.321.pdf), [[code]]([https://www.github](https://github.com/Aolius/semi-fst))\n\n## Evaluation and Analysis\n- Evaluating Style Transfer for Text, NAACL, 2019, [[paper1]](https://arxiv.org/pdf/1904.02295), [[paper2]](https://dspace.mit.edu/bitstream/handle/1721.1/119569/1076275047-MIT.pdf?sequence=1)\n- Rethinking Text Attribute Transfer: A Lexical Analysis, INLG, 2019, [[paper]](https://arxiv.org/pdf/1909.12335), [[code]](https://github.com/FranxYao/pivot_analysis)\n- Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer, EMNLP Workshop on Neural Generation and Translation (WNGT), 2019, [[paper]](https://arxiv.org/pdf/1810.11878)\n- The Daunting Task of Real-World Textual Style Transfer Auto-Evaluation, WNGT, 2019, [[paper]](https://arxiv.org/pdf/1910.03747)\n- Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric, Arxiv, 2020, [[paper]](https://arxiv.org/pdf/2004.05001.pdf)\n- What is wrong with style transfer for texts? Arxiv, [[paper]](https://arxiv.org/pdf/1808.04365)\n- Style versus Content: A distinction without a (learnable) difference?, COLING 2020,\t[[paper]](https://www.aclweb.org/anthology/2020.coling-main.197.pdf)\n- Rethinking Sentiment Style Transfer, EMNLP 2021, [[paper]](https://aclanthology.org/2021.findings-emnlp.135.pdf)\n- Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer, EMNLP 2021, [[paper]](https://aclanthology.org/2021.emnlp-main.100.pdf)\n- Does It Capture STEL? A Modular, Similarity-based Linguistic Style Evaluation Framework, EMNLP 2021, [[paper]](https://aclanthology.org/2021.emnlp-main.569.pdf)\n\n## Stylistic Related Papers\n- Controlling Politeness in Neural Machine Translation via Side Constraints, NAACL 2016, [[paper]](https://www.aclweb.org/anthology/N16-1005.pdf)\n- A Study of Style in Machine Translation: Controlling the Formality of Machine Translation Output, EMNLP 2017, [[paper]](https://www.aclweb.org/anthology/D17-1299.pdf)\n- Controlling Linguistic Style Aspects in Neural Language Generation, EMNLP-2017 Workshop, [[paper]](https://arxiv.org/pdf/1707.02633)\n- Is writing style predictive of scientific fraud?, EMNLP-2017 Workshop, [[paper]](http://www.aclweb.org/anthology/W17-4905)\n- Incorporating Pseudo-Parallel Data for Quantifiable Sequence Editing, EMNLP-2018, [[paper]](https://arxiv.org/pdf/1804.07007)\n- Polite Dialogue Generation Without Parallel Data, TACL, [[paper]](https://arxiv.org/pdf/1805.03162)\n- Adversarial Decomposition of Text Representation, Arxiv, [[paper]](https://arxiv.org/pdf/1808.09042)\n- Unsupervised Stylish Image Description Generation via Domain Layer Norm, AAAI 2019, [[paper]](https://arxiv.org/pdf/1809.06214)\n- Transfer Learning for Style-Specific Text Generation, UNK, 2018, [[paper]](https://nips2018creativity.github.io/doc/Transfer%20Learning%20for%20Style-Specific%20Text%20Generation.pdf)\n- Generating lyrics with variational autoencoder and multi-modal artist embeddings, Arxiv, 2018, [[paper]](https://arxiv.org/pdf/1812.08318)\n- Generating Sentences by Editing Prototypes, TACL, 2018, [[paper]](https://www.aclweb.org/anthology/Q18-1031/)\n- ALTER: Auxiliary Text Rewriting Tool for Natural Language Generation, EMNLP, 2019, [[paper]](https://arxiv.org/pdf/1909.06564)\n- Stylized Text Generation Using Wasserstein Autoencoders with a Mixture of Gaussian Prior, Arxiv, 2019, [[paper]](https://arxiv.org/pdf/1911.03828)\n- Adapting Language Models for Non-Parallel Author-Stylized Rewriting, AAAI, 2020 [[paper]](https://arxiv.org/pdf/1909.09962)\n- Structuring Latent Spaces for Stylized Response Generation, EMNLP, 2019, [[paper]](https://arxiv.org/pdf/1909.05361)\n- Complementary Auxiliary Classifiers for Label-Conditional Text Generation, AAAI, 2020, [[paper]](http://people.ee.duke.edu/~lcarin/AAAI_LiY_6828.pdf), [[code]](https://github.com/s1155026040/CARA)\n- Hooks in the Headline: Learning to Generate Headlines with Controlled Styles, ACL, 2020, [[paper]](https://arxiv.org/pdf/2004.01980.pdf)\n- Exploring Contextual Word-level Style Relevance for Unsupervised Style Transfer, ACL, 2020, [[paper]](https://arxiv.org/pdf/2005.02049.pdf)\n- Parallel Data Augmentation for Formality Style Transfer, ACL, 2020, [[paper]](https://arxiv.org/pdf/2005.07522.pdf)\n- Politeness Transfer: A Tag and Generate Approach, ACL, 2020, [[paper]](https://arxiv.org/pdf/2004.14257.pdf)\n- Towards A Friendly Online Community: An Unsupervised Style Transfer Framework for Profanity Redaction, COLING 2020, [[paper]](https://arxiv.org/pdf/2011.00403.pdf)\n- Generating similes effortlessly like a Pro: A Style Transfer Approach for Simile Generation, EMNLP 2020, [[paper]](https://arxiv.org/pdf/2009.08942.pdf)\n- PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction, EMNLP 2020, [[paper]](https://www.aclweb.org/anthology/2020.emnlp-main.602.pdf)\n- Does BERT Learn as Humans Perceive? Understanding Linguistic Styles through Lexica, EMNLP 2021, [[paper]](https://aclanthology.org/2021.emnlp-main.510.pdf)\n\n## Controlled Text Generation (Similar, but not exactly style transfer)\n- Toward Controlled Generation of Text, ICML 2017. [[paper]](https://arxiv.org/pdf/1703.00955.pdf) \n- CTRL: A Conditional Transformer Language Model for Controllable Generation, arXiv 2019. [[paper]](https://arxiv.org/pdf/1909.05858.pdf)\n- Defending Against Neural Fake News, NeurIPS 2019. (about conditional generation of neural fake news) [[paper]](https://arxiv.org/pdf/1905.12616.pdf)\n- Plug and Play Language Models: A Simple Approach to Controlled Text Generation, ICLR 2020. [[paper]](https://openreview.net/pdf?id=H1edEyBKDS)\n- COCON: A Self-Supervised Approach for Controlled Text Generation, ICLR 2021. [[paper]](https://openreview.net/pdf?id=VD_ozqvBy4W)\n- MISS: An Assistant for Multi-Style Simultaneous Translation, EMNLP, 2021. [[paper]](https://aclanthology.org/2021.emnlp-demo.1.pdf)\n# Unsupervised Seq2Seq\n- Unsupervised neural machine translation, 2017. [[paper]](https://arxiv.org/pdf/1710.11041.pdf)\n\n\n# Workshop and Tutorial\n- Stylistic Variation, EMNLP-2017, [[link]](https://sites.google.com/site/workshoponstylisticvariation/)\n- Stylistic Variation, NAACL-HLT-2018, [[link]](https://sites.google.com/view/2ndstylisticvariation/home)\n- Stylized Text Generation, ACL-2020, [[link]](https://sites.google.com/view/2020-stylized-text-generation/tutorial) [[video-part1]](https://vimeo.com/436479481) [[video-part2]](https://www.youtube.com/watch?v=qSbqVjM-Vik)\n\n# Copyright \nBy Zhenxin Fu (fuzhenxin95@gmail.com) from Peking University.  \n**Welcome to open an issue or make a pull request!**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffuzhenxin%2FStyle-Transfer-in-Text","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffuzhenxin%2FStyle-Transfer-in-Text","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffuzhenxin%2FStyle-Transfer-in-Text/lists"}