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 1–50 of 149 papers

TitleStatusHype
Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement LearningCode1
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
Sentence Simplification with Deep Reinforcement LearningCode0
SCAR: Sentence Compression using Autoencoders for ReconstructionCode0
A Novel Metric for Evaluating Semantics PreservationCode0
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular MaximizationCode0
Unsupervised Semantic Abstractive SummarizationCode0
Explicit Sentence Compression for Neural Machine TranslationCode0
Sequence-to-sequence Models for Cache Transition SystemsCode0
Keyphrase Extraction for N-best Reranking in Multi-Sentence CompressionCode0
Contextualized Semantic Distance between Highly Overlapped TextsCode0
Learning How to Simplify From Explicit Labeling of Complex-Simplified Text PairsCode0
Globally Normalized Transition-Based Neural NetworksCode0
Combining Graph Degeneracy and Submodularity for Unsupervised Extractive SummarizationCode0
Sentence Compression for Arbitrary Languages via Multilingual PivotingCode0
SEQ\^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence CompressionCode0
Improving Factual Consistency in Summarization with Compression-Based Post-EditingCode0
Evaluation Discrepancy Discovery: A Sentence Compression Case-studyCode0
SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence CompressionCode0
Unsupervised Sentence Compression using Denoising Auto-EncodersCode0
An Operation Network for Abstractive Sentence Compression—0
Annotating and Predicting Non-Restrictive Noun Phrase Modifications—0
Adversarial Neural Networks for Cross-lingual Sequence Tagging—0
Automatic Speech Summarisation: A Scoping Review—0
Bayesian Symbol-Refined Tree Substitution Grammars for Syntactic Parsing—0
Can Syntax Help? Improving an LSTM-based Sentence Compression Model for New Domains—0
Cascaded Attention based Unsupervised Information Distillation for Compressive Summarization—0
CoastalCPH at SemEval-2016 Task 11: The importance of designing your Neural Networks right—0
Automatic Grammatical Error Correction for Sequence-to-sequence Text Generation: An Empirical Study—0
An Eye-tracking Study of Named Entity Annotation—0
AutoBreach: Universal and Adaptive Jailbreaking with Efficient Wordplay-Guided Optimization—0
A Two-step Approach to Sentence Compression of Spoken Utterances—0
A New Annotated Portuguese/Spanish Corpus for the Multi-Sentence Compression Task—0
A Difference-of-Convex Programming Approach With Parallel Branch-and-Bound For Sentence Compression Via A Hybrid Extractive Model—0
Abstractive Unsupervised Multi-Document Summarization using Paraphrastic Sentence Fusion—0
A Token-wise CNN-based Method for Sentence Compression—0
A Simple Yet Effective Corpus Construction Method for Chinese Sentence Compression—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
Domain-Specific Image Captioning—0
Document Summarization via Guided Sentence Compression—0
Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction—0
A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization—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
Deleter: Leveraging BERT to Perform Unsupervised Successive Text Compression—0
Event-Driven Headline Generation—0
Deep Learning Approaches to Text Production—0
Extracting token-level signals of syntactic processing from fMRI - with an application to PoS induction—0
A Proposition-Based Abstractive Summariser—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