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
ED-FAITH: Evaluating Dialogue Summarization on Faithfulness—0
Novel Chapter Abstractive Summarization using Spinal Tree Aware Sub-Sentential Content Selection—0
FRSUM: Towards Faithful Abstractive Summarization via Enhancing Factual Robustness—0
Automatic Generation of Abstracts for Research Papers—0
Questioning the Validity of Summarization Datasets and Improving Their Factual Consistency—0
Improving abstractive summarization with energy-based re-rankingCode0
CrisisLTLSum: A Benchmark for Local Crisis Event Timeline Extraction and SummarizationCode0
Universal Evasion Attacks on Summarization ScoringCode0
Towards Summary Candidates FusionCode0
Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based MethodsCode0
Shortcomings of Question Answering Based Factuality Frameworks for Error LocalizationCode0
Just ClozE! A Novel Framework for Evaluating the Factual Consistency Faster in Abstractive SummarizationCode0
Probing of Quantitative Values in Abstractive Summarization Models—0
Abstractive Approaches To Multidocument Summarization Of Medical Literature Reviews—0
Faithful Abstractive Summarization via Fact-aware Consistency-constrained TransformerCode0
LipKey: A Large-Scale News Dataset for Absent Keyphrases Generation and Abstractive Summarization—0
Source-summary Entity Aggregation in Abstractive Summarization—0
Out-of-Distribution Detection and Selective Generation for Conditional Language Models—0
Calibrating Sequence likelihood Improves Conditional Language Generation—0
A Step-by-Step Gradient Penalty with Similarity Calculation for Text Summary GenerationCode0
Harnessing Abstractive Summarization for Fact-Checked Claim DetectionCode0
Applying Transformer-based Text Summarization for Keyphrase Generation—0
Entity-based SpanCopy for Abstractive Summarization to Improve the Factual ConsistencyCode0
Entity-based De-noising Modeling for Controllable Dialogue Summarization—0
Enhancing Semantic Understanding with Self-supervised Methods for Abstractive Dialogue Summarization—0
To Adapt or to Fine-tune: A Case Study on Abstractive SummarizationCode0
Forming Trees with Treeformers—0
Meta-Learning the Difference: Preparing Large Language Models for Efficient AdaptationCode0
Improving the Faithfulness of Abstractive Summarization via Entity Coverage Control—0
DACSA: A large-scale Dataset for Automatic summarization of Catalan and Spanish newspaper Articles—0
Jointly Learning Guidance Induction and Faithful Summary Generation via Conditional Variational Autoencoders—0
Semantic-Preserving Abstractive Text Summarization with Siamese Generative Adversarial Net—0
Few-shot fine-tuning SOTA summarization models for medical dialogues—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
Indian Legal Text Summarization: A Text Normalisation-based Approach—0
The Bull and the Bear: Summarizing Stock Market Discussions—0
CATAMARAN: A Cross-lingual Long Text Abstractive Summarization Dataset—0
Multilingual Text Summarization on Financial Documents—0
Extractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek—0
Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text SummarizationCode0
TeSum: Human-Generated Abstractive Summarization Corpus for TeluguCode0
Multilingual Financial Documentation Summarization by Team_Tredence for FNS2022—0
Counterfactual Data Augmentation improves Factuality of Abstractive Summarization—0
Lossless Acceleration for Seq2seq Generation with Aggressive DecodingCode0
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in SummarizationCode0
Few-shot Mining of Naturally Occurring Inputs and Outputs—0
Efficient Few-Shot Fine-Tuning for Opinion SummarizationCode0
NLPOP: a Dataset for Popularity Prediction of Promoted NLP Research on TwitterCode0
FilipN@LT-EDI-ACL2022-Detecting signs of Depression from Social Media: Examining the use of summarization methods as data augmentation for text classificationCode0
RNSum: A Large-Scale Dataset for Automatic Release Note Generation via Commit Logs Summarization—0
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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