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 61–70 of 149 papers

TitleStatusHype
Human acceptability judgements for extractive sentence compression—0
Identification and Characterization of Newsworthy Verbs in World News—0
Acquisition of Syntactic Simplification Rules for French—0
Abstractive Compression of Captions with Attentive Recurrent Neural Networks—0
Improving Multi-documents Summarization by Sentence Compression based on Expanded Constituent Parse Trees—0
Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention—0
Improving sentence compression by learning to predict gaze—0
InstructCMP: Length Control in Sentence Compression through Instruction-based Large Language Models—0
Japanese Sentence Compression with a Large Training Dataset—0
Joint Decoding of Tree Transduction Models for Sentence Compression—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