Unsupervised Text Style Transfer

21 papers with code • 3 benchmarks • 2 datasets

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Most implemented papers

Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer

lijuncen/Sentiment-and-Style-Transfer NAACL 2018

We consider the task of text attribute transfer: transforming a sentence to alter a specific attribute (e. g., sentiment) while preserving its attribute-independent content (e. g., changing "screen is just the right size" to "screen is too small").

A Probabilistic Formulation of Unsupervised Text Style Transfer

cindyxinyiwang/deep-latent-sequence-model ICLR 2020

Across all style transfer tasks, our approach yields substantial gains over state-of-the-art non-generative baselines, including the state-of-the-art unsupervised machine translation techniques that our approach generalizes.

Structured Content Preservation for Unsupervised Text Style Transfer

YouzhiTian/Structured-Content-Preservation-for-Unsupervised-Text-Style-Transfer 15 Oct 2018

Text style transfer aims to modify the style of a sentence while keeping its content unchanged.

A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer

luofuli/DualLanST 24 May 2019

Therefore, in this paper, we propose a dual reinforcement learning framework to directly transfer the style of the text via a one-step mapping model, without any separation of content and style.

Unsupervised Text Style Transfer using Language Models as Discriminators

asyml/texar NeurIPS 2018

Binary classifiers are often employed as discriminators in GAN-based unsupervised style transfer systems to ensure that transferred sentences are similar to sentences in the target domain.

Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning

dayihengliu/Fine-Grained-Style-Transfer 29 May 2019

We propose a new framework that utilizes the gradients to revise the sentence in a continuous space during inference to achieve text style transfer.

A Hierarchical Reinforced Sequence Operation Method for Unsupervised Text Style Transfer

ChenWu98/Point-Then-Operate ACL 2019

Unsupervised text style transfer aims to alter text styles while preserving the content, without aligned data for supervision.

Semi-supervised Formality Style Transfer using Language Model Discriminator and Mutual Information Maximization

GT-SALT/FormalityStyleTransfer Findings of the Association for Computational Linguistics 2020

Formality style transfer is the task of converting informal sentences to grammatically-correct formal sentences, which can be used to improve performance of many downstream NLP tasks.

LEWIS: Levenshtein Editing for Unsupervised Text Style Transfer

machelreid/lewis Findings (ACL) 2021

Moreover, compared to previous methods on unsupervised data synthesis, our method results in higher quality parallel style pairs and improves model performance.