SOTAVerified

Text Style Transfer

Text Style Transfer is the task of controlling certain attributes of generated text. The state-of-the-art methods can be categorized into two main types which are used on parallel and non-parallel data. Methods on parallel data are typically supervised methods that use a neural sequence-to-sequence model with the encoder-decoder architecture. Methods on non-parallel data are usually unsupervised approaches using Disentanglement, Prototype Editing and Pseudo-Parallel Corpus Construction.

The popular benchmark for this task is the Yelp Review Dataset. Models are typically evaluated with the metrics of Sentiment Accuracy, BLEU, and PPL.

Papers

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Showing 51–100 of 186 papers

TitleStatusHype
Multilingual Text Style Transfer: Datasets & Models for Indian LanguagesCode0
Improving Long Text Understanding with Knowledge Distilled from Summarization Model—0
LMStyle Benchmark: Evaluating Text Style Transfer for Chatbots—0
Distilling Text Style Transfer With Self-Explanation From LLMs—0
Unsupervised Text Style Transfer via LLMs and Attention Masking with Multi-way Interactions—0
Text Detoxification as Style Transfer in English and HindiCode0
Exploring Methods for Cross-lingual Text Style Transfer: The Case of Text Detoxification—0
PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style TransferCode0
STEER: Unified Style Transfer with Expert ReinforcementCode0
Text Fact TransferCode0
Prefix-Tuning Based Unsupervised Text Style Transfer—0
Specializing Small Language Models towards Complex Style Transfer via Latent Attribute Pre-TrainingCode0
Unsupervised Text Style Transfer with Deep Generative Models—0
Text Style Transfer Evaluation Using Large Language Models—0
Don't lose the message while paraphrasing: A study on content preserving style transferCode0
Learning Evaluation Models from Large Language Models for Sequence GenerationCode0
FASTER: A Font-Agnostic Scene Text Editing and Rendering Framework—0
MSSRNet: Manipulating Sequential Style Representation for Unsupervised Text Style TransferCode0
Identifying the style by a qualified reader on a short fragment of generated poetryCode0
Text Style Transfer Back-TranslationCode0
A Call for Standardization and Validation of Text Style Transfer Evaluation—0
Balancing Effect of Training Dataset Distribution of Multiple Styles for Multi-Style Text Transfer—0
Adapter-TST: A Parameter Efficient Method for Multiple-Attribute Text Style Transfer—0
Multidimensional Evaluation for Text Style Transfer Using ChatGPTCode0
Conversation Style Transfer using Few-Shot Learning—0
Style-transfer counterfactual explanations: An application to mortality prevention of ICU patientsCode0
SimpleStyle: An Adaptable Style Transfer Approach—0
Pay Attention to Your Tone: Introducing a New Dataset for Polite Language RewriteCode0
StyleFlow: Disentangle Latent Representations via Normalizing Flow for Unsupervised Text Style Transfer—0
T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation—0
Replacing Language Model for Style TransferCode0
On Text Style Transfer via Style Masked Language Models—0
GenText: Unsupervised Artistic Text Generation via Decoupled Font and Texture Manipulation—0
Text Style Transfer via Optimal Transport—0
Don’t Take It Literally: An Edit-Invariant Sequence Loss for Text GenerationCode0
Studying the role of named entities for content preservation in text style transferCode0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Learning from Bootstrapping and Stepwise Reinforcement Reward: A Semi-Supervised Framework for Text Style TransferCode0
Towards Robust and Semantically Organised Latent Representations for Unsupervised Text Style TransferCode0
A Study on Manual and Automatic Evaluation for Text Style Transfer: The Case of Detoxification—0
Non-Parallel Text Style Transfer with Self-Parallel SupervisionCode0
Efficient Reinforcement Learning for Unsupervised Controlled Text Generation—0
Human Judgement as a Compass to Navigate Automatic Metrics for Formality TransferCode0
Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style TransferCode0
Variational Autoencoder with Disentanglement Priors for Low-Resource Task-Specific Natural Language GenerationCode0
Gradient-guided Unsupervised Text Style Transfer via Contrastive Learning—0
Text Style Transfer for Bias Mitigation using Masked Language Modeling—0
Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation—0
Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Rethinking Style Transformer by Energy-based Interpretation: Adversarial Unsupervised Style Transfer using Pretrained Model—0
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All datasetsYelp Review Dataset (Small)Yelp Review Dataset (Large)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAE+DiscriminatorG-Score (BLEU, Accuracy)74.56—Unverified
2LatentOps (Few shot)G-Score (BLEU, Accuracy)71.6—Unverified
3SentiIncG-Score (BLEU, Accuracy)66.25—Unverified
4DeleteAndRetrieveG-Score (BLEU, Accuracy)54.64—Unverified
5DeleteOnlyG-Score (BLEU, Accuracy)54.11—Unverified
6MultiDecoderG-Score (BLEU, Accuracy)45.02—Unverified
7CAEG-Score (BLEU, Accuracy)38.66—Unverified
8StyleEmbeddingG-Score (BLEU, Accuracy)31.31—Unverified
#ModelMetricClaimedVerifiedStatus
1SentiIncG-Score (BLEU, Accuracy)59.17—Unverified
2StyleEmbBLEU30—Unverified