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Abstractive Text Summarization

Abstractive Text Summarization is the task of generating a short and concise summary that captures the salient ideas of the source text. The generated summaries potentially contain new phrases and sentences that may not appear in the source text.

Source: Generative Adversarial Network for Abstractive Text Summarization

Image credit: Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond

Papers

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Showing 501–550 of 846 papers

TitleStatusHype
Cross-lingual Transfer of Abstractive Summarizer to Less-resource Language—0
Using multiple ASR hypotheses to boost i18n NLU performance—0
An Enhanced MeanSum Method For Generating Hotel Multi-Review Summarizations—0
Bengali Abstractive News Summarization(BANS): A Neural Attention ApproachCode0
Towards Generating Query to Perform Query Focused Abstractive Summarization using Pre-trained ModelCode0
Task Proposal: Abstractive Snippet Generation for Web Pages—0
Distinctive Slogan Generation with Reconstruction—0
SumTitles: a Summarization Dataset with Low Extractiveness—0
Flight of the PEGASUS? Comparing Transformers on Few-shot and Zero-shot Multi-document Abstractive SummarizationCode0
DebateSum: A large-scale argument mining and summarization datasetCode1
Automatic Summarization of Open-Domain Podcast Episodes—0
Detecting Hallucinated Content in Conditional Neural Sequence GenerationCode1
Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles—0
WSL-DS: Weakly Supervised Learning with Distant Supervision for Query Focused Multi-Document Abstractive SummarizationCode0
Liputan6: A Large-scale Indonesian Dataset for Text SummarizationCode1
Divide and Conquer: From Complexity to Simplicity for Lay SummarizationCode0
CIST@CL-SciSumm 2020, LongSumm 2020: Automatic Scientific Document Summarization—0
Using Pre-Trained Transformer for Better Lay Summarization—0
ProphetNet: Predicting Future N-gram for Sequence-to-SequencePre-trainingCode0
Friendly Topic Assistant for Transformer Based Abstractive Summarization—0
TESA: A Task in Entity Semantic Aggregation for Abstractive Summarization—0
PALM: Pre-training an Autoencoding\&Autoregressive Language Model for Context-conditioned Generation—0
Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained GenerationCode1
Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation—0
Learning to Summarize Long Texts with Memory Compression and Transfer—0
Topic-Guided Abstractive Text Summarization: a Joint Learning ApproachCode1
Factual Error Correction for Abstractive Summarization ModelsCode1
Lexicon-constrained Copying Network for Chinese Abstractive Summarization—0
GSum: A General Framework for Guided Neural Abstractive SummarizationCode1
MAST: Multimodal Abstractive Summarization with Trimodal Hierarchical AttentionCode1
Understanding Neural Abstractive Summarization Models via UncertaintyCode1
Multi-Task Learning for Cross-Lingual Abstractive Summarization—0
Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised ApproachCode1
Q-learning with Language Model for Edit-based Unsupervised SummarizationCode1
Multi-hop Inference for Question-driven SummarizationCode0
A Cascade Approach to Neural Abstractive Summarization with Content Selection and FusionCode0
WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive SummarizationCode1
Multi-Fact Correction in Abstractive Text Summarization—0
基于统一模型的藏文新闻摘要(Abstractive Summarization of Tibetan News Based on Hybrid Model)—0
Reducing Quantity Hallucinations in Abstractive SummarizationCode0
Global-aware Beam Search for Neural Abstractive SummarizationCode0
Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document SummarizationCode1
A Baseline Analysis for Podcast Abstractive SummarizationCode0
Abstractive Summarization of Spoken andWritten Instructions with BERTCode2
Abstractive Summarization of Spoken and Written Instructions with BERTCode1
Generating Categories for Sets of Entities—0
Better Fine-Tuning by Reducing Representational CollapseCode1
Leverage Unlabeled Data for Abstractive Speech Summarization with Self-Supervised Learning and Back-Summarization—0
Sequence Generation with Mixed RepresentationsCode1
Composing Elementary Discourse Units in Abstractive Summarization—0
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All datasetsCNN / Daily MailAbstractive Text Summarization from Il PostvietnewsAbstractive Text Summarization from FanpageEDUsumCNN/Daily MailMLSum-itWITSAESLCeLifeInshorts NewsMLSUM de

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Scrambled code + broken (alter)ROUGE-148.18—Unverified
2BRIOROUGE-147.78—Unverified
3PegasusROUGE-147.36—Unverified
4PEGASUS + SummaRerankerROUGE-147.16—Unverified
5Scrambled code + brokenROUGE-146.71—Unverified
6BART + SimCLSROUGE-146.67—Unverified
7SEASONROUGE-146.27—Unverified
8Fourier TransformerROUGE-144.76—Unverified
9GLM-XXLargeROUGE-144.7—Unverified
10BART + R-DropROUGE-144.51—Unverified
#ModelMetricClaimedVerifiedStatus
1mBARTROUGE-138.91—Unverified
2mBARTROUGE-138.91—Unverified
3BART-ITROUGE-137.31—Unverified
4mT5ROUGE-135.04—Unverified
5IT5ROUGE-133.78—Unverified
6IT5-baseROUGE-132.88—Unverified
7Pegasus-CNN/DM (eng-it translation)ROUGE-123.96—Unverified
8Pegasus-XSum (eng-it translation)ROUGE-121.03—Unverified
#ModelMetricClaimedVerifiedStatus
1Kết quả nghiên cứuRouge-167.8—Unverified
2ViT5 largeRouge-163.37—Unverified
3ViT5 baseRouge-162.77—Unverified
4BARTphoRouge-161.14—Unverified
5mBARTRouge-159.81—Unverified
6mT5Rouge-158.05—Unverified
7TransformerRouge-157.56—Unverified
#ModelMetricClaimedVerifiedStatus
1mBARTROUGE-136.52—Unverified
2mBARTROUGE-136.5—Unverified
3BART-ITROUGE-135.42—Unverified
4mT5ROUGE-134.13—Unverified
5IT5-baseROUGE-133.99—Unverified
6IT5ROUGE-133.83—Unverified
#ModelMetricClaimedVerifiedStatus
1GP_Step_SimROUGE-164.48—Unverified
2NEZHAROUGE-163.91—Unverified
3RoBERTaROUGE-163.22—Unverified
4BERTROUGE-162.37—Unverified
5Seq2seqROUGE-148.62—Unverified
#ModelMetricClaimedVerifiedStatus
1BART (TextBox 2.0)ROUGE-144.47—Unverified
2SEGMENTROUGE-142.1—Unverified
3CriSPO 3-shotROUGE-142.1—Unverified
4Claude Instant + SigExtROUGE-142—Unverified
#ModelMetricClaimedVerifiedStatus
1mBARTrouge119.35—Unverified
2IT5rouge119.29—Unverified
3Pegasus-CNN/DM (eng-it translation)rouge116.97—Unverified
4Pegasus-XSum (eng-it translation)rouge115.17—Unverified
#ModelMetricClaimedVerifiedStatus
1BART-ITROUGE-142.32—Unverified
2mT5ROUGE-140.6—Unverified
3mBARTROUGE-139.32—Unverified
4IT5-baseROUGE-137.98—Unverified
#ModelMetricClaimedVerifiedStatus
1PEGASUSROUGE-137.68—Unverified
2Multi-Stage Extractor/AbstractorROUGE-123.67—Unverified
#ModelMetricClaimedVerifiedStatus
1Two stage LLMsTest ROGUE-10.46—Unverified
#ModelMetricClaimedVerifiedStatus
1T2SAMROUGE48.5—Unverified
#ModelMetricClaimedVerifiedStatus
1mBARTMETEOR0.44—Unverified
#ModelMetricClaimedVerifiedStatus
1mBARTMETEOR0.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Two stage LLMsTest ROGUE-10.44—Unverified
#ModelMetricClaimedVerifiedStatus
1BertSumContent F129.8—Unverified