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 351–400 of 846 papers

TitleStatusHype
A Zero-Resource Approach to Cross-Lingual Query-Focused Abstractive Summarization—0
A Unified and Efficient Contrastive Learning Framework for Text Summarization—0
Controlling Pretrained Language Generation Models by Learning to Focus—0
Improving the Faithfulness of Abstractive Summarization via Entity Coverage Control—0
MoFE: Mixture of Factual Experts for Controlling Hallucinations in Abstractive Summarization—0
Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and DocumentsCode0
SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization—0
Incorporating Question Answering-Based Signals into Abstractive Summarization via Salient Span Selection—0
Just Ask! Evaluating Machine Translation by Asking and Answering QuestionsCode0
Sentence-level Planning for Especially Abstractive SummarizationCode0
A Novel Wikipedia based Dataset for Monolingual and Cross-Lingual SummarizationCode0
Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization—0
EASE: Extractive-Abstractive Summarization End-to-End using the Information Bottleneck Principle—0
Q^2: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering—0
AUTOSUMM: Automatic Model Creation for Text Summarization—0
Learn to Copy from the Copying History: Correlational Copy Network for Abstractive SummarizationCode0
GupShup: Summarizing Open-Domain Code-Switched ConversationsCode1
Gradient-Based Adversarial Factual Consistency Evaluation for Abstractive Summarization—0
Fine-grained Factual Consistency Assessment for Abstractive Summarization Models—0
Event Graph based Sentence Fusion—0
Integrating Semantic Scenario and Word Relations for Abstractive Sentence Summarization—0
Using Question Answering Rewards to Improve Abstractive SummarizationCode0
ForumSum: A Multi-Speaker Conversation Summarization Dataset—0
Exploring Multitask Learning for Low-Resource Abstractive SummarizationCode0
A Finer-grain Universal Dialogue Semantic Structures based Model For Abstractive Dialogue Summarization—0
Summarization of German Court RulingsCode0
s2s-ft: Fine-Tuning Pretrained Transformer Encoders for Sequence-to-Sequence Learning—0
Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization—0
Learning Rich Representation of Keyphrases from Text—0
Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization—0
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue—0
Attention Temperature Matters in Abstractive Summarization Distillation—0
ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation—0
Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and DocumentsCode1
PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document SummarizationCode1
Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine TranslationCode1
Control Prefixes for Parameter-Efficient Text GenerationCode1
Modeling Endorsement for Multi-Document Abstractive SummarizationCode0
DYLE: Dynamic Latent Extraction for Abstractive Long-Input SummarizationCode1
CaPE: Contrastive Parameter Ensembling for Reducing Hallucination in Abstractive Summarization—0
Enhance Long Text Understanding via Distilled Gist Detector from Abstractive Summarization—0
HydraSum: Disentangling Stylistic Features in Text Summarization using Multi-Decoder ModelsCode1
VieSum: How Robust Are Transformer-based Models on Vietnamese Summarization?—0
HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow ArticlesCode1
Target-Side Data Augmentation for Sequence GenerationCode1
HydraSum - Disentangling Stylistic Features in Text Summarization using Multi-Decoder Models—0
DictFormer: Tiny Transformer with Shared Dictionary—0
Enriching and Controlling Global Semantics for Text Summarization—0
Recursively Summarizing Books with Human Feedback—0
BARTpho: Pre-trained Sequence-to-Sequence Models for VietnameseCode1
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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