SOTAVerified

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 301–350 of 846 papers

TitleStatusHype
Improving the Factual Accuracy of Abstractive Clinical Text Summarization using Multi-Objective Optimization—0
BRIO: Bringing Order to Abstractive SummarizationCode2
Entity-driven Fact-aware Abstractive Summarization of Biomedical LiteratureCode0
Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq GenerationCode1
Linearizing Transformer with Key-Value Memory—0
Towards Abstractive Grounded Summarization of Podcast TranscriptsCode1
AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization—0
Meta-X_NLG: A Meta-Learning Approach Based on Language Clustering for Zero-Shot Cross-Lingual Transfer and GenerationCode0
ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence GenerationCode1
An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Models—0
Don't Say What You Don't Know: Improving the Consistency of Abstractive Summarization by Constraining Beam SearchCode0
Differentiable Multi-Agent Actor-Critic for Multi-Step Radiology Report Summarization—0
SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive SummarizationCode1
Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods—0
ClueGraphSum: Let Key Clues Guide the Cross-Lingual Abstractive Summarization—0
Controlling the Focus of Pretrained Language Generation ModelsCode0
Learning Cluster Patterns for Abstractive Summarization—0
Sequence-to-Sequence Resources for CatalanCode0
Survey of Hallucination in Natural Language Generation—0
Differentiable N-gram Objective on Abstractive SummarizationCode0
Locally Typical SamplingCode4
Submodularity In Machine Learning and Artificial Intelligence—0
Unsupervised Multi-Granularity SummarizationCode1
AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization—0
Exploring Cross-Lingual Guidance in Abstractive Summarization—0
Incorporating Question Answering-Based Signals into Abstractive Summarization via Salient Span Selection—0
Controlling the Focus of Pretrained Language Generation Models—0
Topic-controllable Abstractive Summarization—0
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization—0
BOOKSUM: A Collection of Datasets for Long-form Narrative Summarization—0
Measuring Faithfulness of Abstractive Summaries—0
Mosaic Augmentation for Text: Cropping and Collaging as Cross-Domain Techniques—0
Novel Chapter Abstractive Summarization using Spinal Tree Aware Sub-Sentential Content Selection—0
ExtraPhrase: Efficient Data Augmentation for Abstractive Summarization—0
Adaptive Beam Search to Enhance On-device Abstractive Summarization—0
Domain Adaptation with Pre-trained Transformers for Query Focused Abstractive Text SummarizationCode0
May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation—0
Learning Rich Representation of Keyphrases from TextCode1
CrossSum: Beyond English-Centric Cross-Lingual Summarization for 1,500+ Language PairsCode1
LongT5: Efficient Text-To-Text Transformer for Long SequencesCode1
Reinforced Abstractive Summarization with Adaptive Length Controlling—0
CO2Sum:Contrastive Learning for Factual-Consistent Abstractive Summarization—0
Abstractive Text Summarization: Enhancing Sequence-to-Sequence Models Using Word Sense Disambiguation and Semantic Content Generalization—0
Controlling Conditional Language Models without Catastrophic ForgettingCode1
New Approaches to Long Document Summarization: Fourier Transform Based Attention in a Transformer Model—0
Pointer over Attention: An Improved Bangla Text Summarization Approach Using Hybrid Pointer Generator Network—0
Generating Diverse and High-Quality Abstractive Summaries with Variational Transformers—0
A Zero-Resource Approach to Cross-Lingual Query-Focused Abstractive Summarization—0
Generation of News Articles from Tweets : An Experiment—0
A Unified and Efficient Contrastive Learning Framework for Text 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