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
Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement LearningCode1
Non-Autoregressive Text Generation with Pre-trained Language ModelsCode1
Syntactically Look-Ahead Attention Network for Sentence CompressionCode1
Tiny Transformers Excel at Sentence Compression—0
Target-Aware Language Modeling via Granular Data Sampling—0
InstructCMP: Length Control in Sentence Compression through Instruction-based Large Language Models—0
AutoBreach: Universal and Adaptive Jailbreaking with Efficient Wordplay-Guided Optimization—0
From Lengthy to Lucid: A Systematic Literature Review on NLP Techniques for Taming Long Sentences—0
Reconstruct Before Summarize: An Efficient Two-Step Framework for Condensing and Summarizing Meeting Transcripts—0
Improving Factual Consistency in Summarization with Compression-Based Post-EditingCode0
A Simple Yet Effective Corpus Construction Method for Chinese Sentence Compression—0
SOM-NCSCM : An Efficient Neural Chinese Sentence Compression Model Enhanced with Self-Organizing Map—0
A Novel Metric for Evaluating Semantics PreservationCode0
Leveraging Information Bottleneck for Scientific Document Summarization—0
Contextualized Semantic Distance between Highly Overlapped TextsCode0
Cross-Register Projection for Headline Part of Speech Tagging—0
RepSum: Unsupervised Dialogue Summarization based on Replacement Strategy—0
Etat de l’art en compression multi-phrases pour la synthèse de documents (State-of-the-art of multi-sentence compression for document summarization)—0
With Measured Words: Simple Sentence Selection for Black-Box Optimization of Sentence Compression Algorithms—0
Evaluation Discrepancy Discovery: A Sentence Compression Case-studyCode0
Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention—0
A Token-wise CNN-based Method for Sentence Compression—0
Automatic Speech Summarisation: A Scoping Review—0
SCAR: Sentence Compression using Autoencoders for ReconstructionCode0
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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