Papers Sentence ReWriting
“Sentence ReWriting” 태그가 달린 논문 15편 · 필터 해제
RewriteLM: An Instruction-Tuned Large Language Model for Text Rewriting
Large Language Models (LLMs) have demonstrated impressive capabilities in creative tasks such as storytelling and E-mail generation. However, as LLMs are primarily trained on final text results rather than intermediate r…
Language ModelingLanguage ModellingLarge Language ModelSentence+2GEMINI: Controlling the Sentence-level Writing Style for Abstractive Text Summarization
Human experts write summaries using different techniques, including extracting a sentence from the document and rewriting it, or fusing various information from the document to abstract it. These techniques are flexible …
Abstractive Text SummarizationSentenceSentence ReWritingText SummarizationRefined Vision-Language Modeling for Fine-grained Multi-modal Pre-training
Fine-grained supervision based on object annotations has been widely used for vision and language pre-training (VLP). However, in real-world application scenarios, aligned multi-modal data is usually in the image-caption…
Image-text matchingLanguage ModelingLanguage ModellingObject+3Towards Document-Level Paraphrase Generation with Sentence Rewriting and Reordering
Paraphrase generation is an important task in natural language processing. Previous works focus on sentence-level paraphrase generation, while ignoring document-level paraphrase generation, which is a more challenging an…
DiversityParaphrase GenerationSentenceSentence ReWritingA Recipe For Arbitrary Text Style Transfer with Large Language Models
In this paper, we leverage large language models (LMs) to perform zero-shot text style transfer. We present a prompting method that we call augmented zero-shot learning, which frames style transfer as a sentence rewritin…
SentenceSentence ReWritingStyle TransferText Style Transfer+1Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision
Despite recent success in machine reading comprehension (MRC), learning high-quality MRC models still requires large-scale labeled training data, even using strong pre-trained language models (PLMs). The pre-training tas…
Language ModelingLanguage ModellingMachine Reading ComprehensionQuestion Answering+4A Recipe For Arbitrary Text Style Transfer with Large Language Models
In this paper, we leverage large language models (LLMs) to perform zero-shot text style transfer. We present a prompting method that we call augmented zero-shot learning, which frames style transfer as a sentence rewriti…
SentenceSentence ReWritingStyle TransferText Style Transfer+1Towards Clinical Encounter Summarization: Learning to Compose Discharge Summaries from Prior Notes
The records of a clinical encounter can be extensive and complex, thus placing a premium on tools that can extract and summarize relevant information. This paper introduces the task of generating discharge summaries for …
HallucinationInformativenessSentenceSentence ReWritingR&R: Metric-guided Adversarial Sentence Generation
Adversarial examples are helpful for analyzing and improving the robustness of text classifiers. Generating high-quality adversarial examples is a challenging task as it requires generating fluent adversarial sentences t…
Adversarial AttackGeneral ClassificationSemantic SimilaritySemantic Textual Similarity+4Summary Level Training of Sentence Rewriting for Abstractive Summarization
As an attempt to combine extractive and abstractive summarization, Sentence Rewriting models adopt the strategy of extracting salient sentences from a document first and then paraphrasing the selected ones to generate a …
Abstractive Text SummarizationExtractive Text SummarizationNatural Language UnderstandingReinforcement Learning+2Sequence-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+2ParaBank: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-constrained Neural Machine Translation
We present ParaBank, a large-scale English paraphrase dataset that surpasses prior work in both quantity and quality. Following the approach of ParaNMT, we train a Czech-English neural machine translation (NMT) system to…
DiversityMachine TranslationNMTSemantic Similarity+4Sentence Rewriting for Semantic Parsing
A major challenge of semantic parsing is the vocabulary mismatch problem between natural language and target ontology. In this paper, we propose a sentence rewriting based semantic parsing method, which can effectively r…
FormSemantic ParsingSentenceSentence ReWritingLanguage Style Transfer from Sentences with Arbitrary Unknown Styles
Language style transfer is the problem of migrating the content of a source sentence to a target style. In many of its applications, parallel training data are not available and source sentences to be transferred may hav…
SentenceSentence ReWritingStyle TransferFast Abstractive Summarization with Reinforce-Selected Sentence Rewriting
Inspired by how humans summarize long documents, we propose an accurate and fast summarization model that first selects salient sentences and then rewrites them abstractively (i.e., compresses and paraphrases) to generat…
Abstractive Text SummarizationDecoderSentenceSentence ReWriting+1