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 51–60 of 149 papers

TitleStatusHype
Adversarial Neural Networks for Cross-lingual Sequence Tagging—0
An Operation Network for Abstractive Sentence Compression—0
Abstractive Unsupervised Multi-Document Summarization using Paraphrastic Sentence Fusion—0
Sequence-to-sequence Models for Cache Transition SystemsCode0
Unsupervised Semantic Abstractive SummarizationCode0
A Language Model based Evaluator for Sentence Compression—0
Higher-Order Syntactic Attention Network for Longer Sentence Compression—0
Deep Learning Approaches to Text Production—0
Multi-Sentence Compression with Word Vertex-Labeled Graphs and Integer Linear Programming—0
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular MaximizationCode0
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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