Sentence Compression

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

22 shown of 22 papers with code (149 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
  14 May 2018 4 repositories listed
  We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations.
• Keyphrase Extraction for N-best Reranking in Multi-Sentence Compression
  1 Jun 2013 2 repositories listed
• Improving Factual Consistency in Summarization with Compression-Based Post-Editing
  11 Nov 2022 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  We propose to use sentence-compression data to train the post-editing model to take a summary with extrinsic entity errors marked with special tokens and output a compressed, well-formed summary with those errors…
• Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion
  26 May 2022 1 repository listed
  We advance the state-of-the-art in unsupervised abstractive dialogue summarization by utilizing multi-sentence compression graphs.
• Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement Learning
  17 May 2022 1 repository listed
  Sentence compression reduces the length of text by removing non-essential content while preserving important facts and grammaticality.
• A Novel Metric for Evaluating Semantics Preservation
  16 Oct 2021 1 repository listed
  By exploiting the property of NDD, we implement a unsupervised and even training-free algorithm for extractive sentence compression.
• Contextualized Semantic Distance between Highly Overlapped Texts
  4 Oct 2021 1 repository listed
  Overlapping frequently occurs in paired texts in natural language processing tasks like text editing and semantic similarity evaluation.
• Non-Autoregressive Text Generation with Pre-trained Language Models
  16 Feb 2021 1 repository listed
  In this work, we show that BERT can be employed as the backbone of a NAG model to greatly improve performance.
• Evaluation Discrepancy Discovery: A Sentence Compression Case-study
  22 Jan 2021 1 repository listed
  Reliable evaluation protocols are of utmost importance for reproducible NLP research.
• SCAR: Sentence Compression using Autoencoders for Reconstruction
  1 Jul 2020 1 repository listed
  The compressor masks the input, and the reconstructor tries to regenerate it.
• Syntactically Look-Ahead Attention Network for Sentence Compression
  4 Feb 2020 1 repository listed
  Sentence compression is the task of compressing a long sentence into a short one by deleting redundant words.
• Explicit Sentence Compression for Neural Machine Translation
  27 Dec 2019 1 repository listed
  In this paper, we propose an explicit sentence compression method to enhance the source sentence representation for NMT.
• SEQ\^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression
  1 Jun 2019 1 repository listed
  The proposed model does not require parallel text-summary pairs, achieving promising results in unsupervised sentence compression on benchmark datasets.
• SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression
  7 Apr 2019 1 repository listed
  The proposed model does not require parallel text-summary pairs, achieving promising results in unsupervised sentence compression on benchmark datasets.
• Sentence Compression for Arbitrary Languages via Multilingual Pivoting
  1 Oct 2018 1 repository listed
  In this paper we advocate the use of bilingual corpora which are abundantly available for training sentence compression models.
• Unsupervised Sentence Compression using Denoising Auto-Encoders
  7 Sep 2018 1 repository listed
  In sentence compression, the task of shortening sentences while retaining the original meaning, models tend to be trained on large corpora containing pairs of verbose and compressed sentences.
• Sequence-to-sequence Models for Cache Transition Systems
  1 Jul 2018 1 repository listed
  In this paper, we present a sequence-to-sequence based approach for mapping natural language sentences to AMR semantic graphs.
• Unsupervised Semantic Abstractive Summarization
  1 Jul 2018 1 repository listed
  Automatic abstractive summary generation remains a significant open problem for natural language processing.
• Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs
  1 Nov 2017 1 repository listed
  Current research in text simplification has been hampered by two central problems: (i) the small amount of high-quality parallel simplification data available, and (ii) the lack of explicit annotations of simplification…
• Combining Graph Degeneracy and Submodularity for Unsupervised Extractive Summarization
  1 Sep 2017 1 repository listed
  We present a fully unsupervised, extractive text summarization system that leverages a submodularity framework introduced by past research.
• Sentence Simplification with Deep Reinforcement Learning
  31 Mar 2017 1 repository listed
  Sentence simplification aims to make sentences easier to read and understand.
• Globally Normalized Transition-Based Neural Networks
  19 Mar 2016 1 repository listed
  Our model is a simple feed-forward neural network that operates on a task-specific transition system, yet achieves comparable or better accuracies than recurrent models.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.