SOTAVerified

Sentence Compression

Sentence Compression is the task of reducing the length of text by removing non-essential content while preserving important facts and grammaticality.

Papers

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Showing 1–25 of 149 papers

TitleStatusHype
Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV ConversionCode1
Syntactically Look-Ahead Attention Network for Sentence CompressionCode1
Non-Autoregressive Text Generation with Pre-trained Language ModelsCode1
Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement LearningCode1
A Difference-of-Convex Programming Approach With Parallel Branch-and-Bound For Sentence Compression Via A Hybrid Extractive Model—0
Adversarial Neural Networks for Cross-lingual Sequence Tagging—0
Abstractive Unsupervised Multi-Document Summarization using Paraphrastic Sentence Fusion—0
A Multilingual Study of Multi-Sentence Compression using Word Vertex-Labeled Graphs and Integer Linear Programming—0
A Dataset and Evaluation Metrics for Abstractive Compression of Sentences and Short Paragraphs—0
Analyse de la r\'egulation de la longueur dans un syst\`eme neuronal de compression de phrase : une \'etude du mod\`ele LenInit (Investigating Length Regulation in a Sentence Compression Neural System : a Study on the LenInit Model)—0
A New Annotated Portuguese/Spanish Corpus for the Multi-Sentence Compression Task—0
An Eye-tracking Study of Named Entity Annotation—0
Annotating and Predicting Non-Restrictive Noun Phrase Modifications—0
An Operation Network for Abstractive Sentence Compression—0
A Language Model based Evaluator for Sentence Compression—0
Abstractive Multi-document Summarization with Semantic Information Extraction—0
A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization—0
Approximation Strategies for Multi-Structure Sentence Compression—0
A Proposition-Based Abstractive Summariser—0
A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization—0
A Simple Yet Effective Corpus Construction Method for Chinese Sentence Compression—0
A Token-wise CNN-based Method for Sentence Compression—0
A Two-step Approach to Sentence Compression of Spoken Utterances—0
AutoBreach: Universal and Adaptive Jailbreaking with Efficient Wordplay-Guided Optimization—0
A Novel Discriminative Framework for Sentence-Level Discourse Analysis—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SLAHAN (LSTM+syntactic-information)F10.86—Unverified
2BiRNN + LM EvaluatorF10.85—Unverified
3Higher-Order Syntactic Attention NetworkF10.84—Unverified
4LSTMF10.82—Unverified
5LSTMs + eye-movementF10.81—Unverified
6BiLSTMF10.8—Unverified