Papers Formality Style Transfer
“Formality Style Transfer” 태그가 달린 논문 19편 · 필터 해제
Formality Style Transfer in Persian
This study explores the formality style transfer in Persian, particularly relevant in the face of the increasing prevalence of informal language on digital platforms, which poses challenges for existing Natural Language …
Formality Style TransferNavigateStyle TransferICLEF: In-Context Learning with Expert Feedback for Explainable Style Transfer
While state-of-the-art large language models (LLMs) can excel at adapting text from one style to another, current work does not address the explainability of style transfer models. Recent work has explored generating tex…
Authorship AttributionAuthorship VerificationFormality Style TransferIn-Context Learning+1Reducing Sequence Length by Predicting Edit Operations with Large Language Models
Large Language Models (LLMs) have demonstrated remarkable performance in various tasks and gained significant attention. LLMs are also used for local sequence transduction tasks, including grammatical error correction (G…
Formality Style TransferGrammatical Error CorrectionStyle TransferText SimplificationCoEdIT: Text Editing by Task-Specific Instruction Tuning
We introduce CoEdIT, a state-of-the-art text editing system for writing assistance. CoEdIT takes instructions from the user specifying the attributes of the desired text, such as "Make the sentence simpler" or "Write it …
Formality Style TransferGrammatical Error CorrectionLanguage ModelingLarge Language Model+4Semi-Supervised Formality Style Transfer with Consistency Training
Formality style transfer (FST) is a task that involves paraphrasing an informal sentence into a formal one without altering its meaning. To address the data-scarcity problem of existing parallel datasets, previous studie…
Formality Style TransferSentenceEvaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer
While the field of style transfer (ST) has been growing rapidly, it has been hampered by a lack of standardized practices for automatic evaluation. In this paper, we evaluate leading ST automatic metrics on the oft-resea…
Formality Style TransferStyle TransferImproving Formality Style Transfer with Context-Aware Rule Injection
Models pre-trained on large-scale regular text corpora often do not work well for user-generated data where the language styles differ significantly from the mainstream text. Here we present Context-Aware Rule Injection …
DecoderFormality Style TransferSentiment AnalysisStyle TransferOl\'a, Bonjour, Salve! XFORMAL: A Benchmark for Multilingual Formality Style Transfer
We take the first step towards multilingual style transfer by creating and releasing XFORMAL, a benchmark of multiple formal reformulations of informal text in Brazilian Portuguese, French, and Italian. Results on XFORMA…
Formality Style TransferStyle TransferThank you BART! Rewarding Pre-Trained Models Improves Formality Style Transfer
Scarcity of parallel data causes formality style transfer models to have scarce success in preserving content. We show that fine-tuning pre-trained language (GPT-2) and sequence-to-sequence (BART) models boosts content p…
Formality Style TransferStyle TransferXFORMAL: A Benchmark for Multilingual Formality Style Transfer
We take the first step towards multilingual style transfer by creating and releasing XFORMAL, a benchmark of multiple formal reformulations of informal text in Brazilian Portuguese, French, and Italian. Results on XFORMA…
Formality Style TransferStyle TransferFormality Style Transfer with Shared Latent Space
Conventional approaches for formality style transfer borrow models from neural machine translation, which typically requires massive parallel data for training. However, the dataset for formality style transfer is consid…
Formality Style TransferMachine TranslationStyle TransferTranslationSemi-supervised Formality Style Transfer using Language Model Discriminator and Mutual Information Maximization
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. In this work, we propose a semi-supe…
Formality Style TransferLanguage ModelingLanguage ModellingSemi-Supervised Formality Style Transfer+4Parallel Data Augmentation for Formality Style Transfer
The main barrier to progress in the task of Formality Style Transfer is the inadequacy of training data. In this paper, we study how to augment parallel data and propose novel and simple data augmentation methods for thi…
Data AugmentationFormality Style TransferSentenceStyle TransferFormality Style Transfer for Noisy, User-generated Conversations: Extracting Labeled, Parallel Data from Unlabeled Corpora
Typical datasets used for style transfer in NLP contain aligned pairs of two opposite extremes of a style. As each existing dataset is sourced from a specific domain and context, most use cases will have a sizable mismat…
Formality Style TransferSentenceStyle TransferHarnessing Pre-Trained Neural Networks with Rules for Formality Style Transfer
Formality text style transfer plays an important role in various NLP applications, such as non-native speaker assistants and child education. Early studies normalize informal sentences with rules, before statistical and …
Formality Style TransferStyle TransferText Style TransferSequence-to-sequence Pre-training with Data Augmentation for Sentence Rewriting
We study sequence-to-sequence (seq2seq) pre-training with data augmentation for sentence rewriting. Instead of training a seq2seq model with gold training data and augmented data simultaneously, we separate them to train…
Data AugmentationFormality Style TransferGrammatical Error CorrectionSentence+2Automatic Grammatical Error Correction for Sequence-to-sequence Text Generation: An Empirical Study
Sequence-to-sequence (seq2seq) models have achieved tremendous success in text generation tasks. However, there is no guarantee that they can always generate sentences without grammatical errors. In this paper, we presen…
Formality Style TransferGrammatical Error CorrectionMachine TranslationSentence+4Formality Style Transfer with Hybrid Textual Annotations
Formality style transformation is the task of modifying the formality of a given sentence without changing its content. Its challenge is the lack of large-scale sentence-aligned parallel data. In this paper, we propose a…
Formality Style TransferSentenceStyle TransferText Style Transfer+1Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer
Style transfer is the task of automatically transforming a piece of text in one particular style into another. A major barrier to progress in this field has been a lack of training and evaluation datasets, as well as ben…
Formality Style TransferMachine TranslationStyle TransferTranslation