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 1–50 of 149 papers

TitleStatusHype
Non-Autoregressive Text Generation with Pre-trained Language ModelsCode1
Syntactically Look-Ahead Attention Network for Sentence CompressionCode1
Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement LearningCode1
Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV ConversionCode1
Abstractive Unsupervised Multi-Document Summarization using Paraphrastic Sentence Fusion—0
Adversarial Neural Networks for Cross-lingual Sequence Tagging—0
Framework of Automatic Text Summarization Using Reinforcement Learning—0
A Multilingual Study of Multi-Sentence Compression using Word Vertex-Labeled Graphs and Integer Linear Programming—0
Fast k-best Sentence Compression—0
A Dataset and Evaluation Metrics for Abstractive Compression of Sentences and Short Paragraphs—0
A Difference-of-Convex Programming Approach With Parallel Branch-and-Bound For Sentence Compression Via A Hybrid Extractive Model—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
Combining Word Embeddings and N-grams for Unsupervised Document 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
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
AutoBreach: Universal and Adaptive Jailbreaking with Efficient Wordplay-Guided Optimization—0
Automatic Grammatical Error Correction for Sequence-to-sequence Text Generation: An Empirical Study—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
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