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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 149 papers

TitleStatusHype
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
A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization—0
Combining Intra- and Multi-sentential Rhetorical Parsing for Document-level Discourse Analysis—0
A Novel Discriminative Framework for Sentence-Level Discourse Analysis—0
Creating and using large monolingual parallel corpora for sentential paraphrase generation—0
Cross-lingual Transfer of Correlations between Parts of Speech and Gaze Features—0
Cross-Register Projection for Headline Part of Speech Tagging—0
Cross-Task Knowledge Transfer for Query-Based Text Summarization—0
Crowd-Sourced Iterative Annotation for Narrative Summarization Corpora—0
Deep Learning Approaches to Text Production—0
Deleter: Leveraging BERT to Perform Unsupervised Successive Text Compression—0
Document Summarization via Guided Sentence Compression—0
Domain-Specific Image Captioning—0
Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction—0
Acquisition of Syntactic Simplification Rules for French—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
A Token-wise CNN-based Method for Sentence Compression—0
Event-Driven Headline Generation—0
A Two-step Approach to Sentence Compression of Spoken Utterances—0
Extracting token-level signals of syntactic processing from fMRI - with an application to PoS induction—0
Abstractive Compression of Captions with Attentive Recurrent Neural Networks—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