mlsanityData to 7 Oct 2026

Improve Query Focused Abstractive Summarization by Incorporating Answer Relevance

arXiv 2105.12969 ↗First posted 27 May 2021cs.CLcited by 15

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Abstract (arXiv)

Query focused summarization (QFS) models aim to generate summaries from source documents that can answer the given query. Most previous work on QFS only considers the query relevance criterion when producing the summary. However, studying the effect of answer relevance in the summary generating process is also important. In this paper, we propose QFS-BART, a model that incorporates the explicit answer relevance of the source documents given the query via a question answering model, to generate coherent and answer-related summaries. Furthermore, our model can take advantage of large pre-trained models which improve the summarization performance significantly. Empirical results on the Debatepedia dataset show that the proposed model achieves the new state-of-the-art performance.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 29 of its 49 references that are in the map. First posted on arXiv 27 May 2021.

Builds on

29 of 49 references.

References · 29

  1. 2017Attention Is All You Needcited by 59,932
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
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  8. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,308
  9. 2017Get To The Point: Summarization with Pointer-Generator Networkscited by 1,281
  10. 2019PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarizationcited by 1,100
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17 more
  1. 2019Text Summarization with Pretrained Encoderscited by 553
  2. 2017A Deep Reinforced Model for Abstractive Summarizationcited by 364
  3. 2019MASS: Masked Sequence to Sequence Pre-training for Language Generationcited by 345
  4. 2016NewsQA: A Machine Comprehension Datasetcited by 330
  5. 2018Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategiescited by 292
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  8. 2019End-to-End Open-Domain Question Answering with BERTserinicited by 152
  9. 2020CrossNER: Evaluating Cross-Domain Named Entity Recognitioncited by 102
  10. 2021AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarizationcited by 51
  11. 2017Diversity driven Attention Model for Query-based Abstractive Summarizationcited by 42
  12. 2018Query Focused Abstractive Summarization: Incorporating Query Relevance, Multi-Document Coverage, and Summary Length Constraints into seq2seq Modelscited by 39
  13. 2020ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generationcited by 39
  14. 2017A Pilot Study of Domain Adaptation Effect for Neural Abstractive Summarizationcited by 12
  15. 2020Conditional Self-Attention for Query-based Summarizationcited by 6
  16. 2020Query Focused Multi-Document Summarization with Distant Supervisioncited by 6
  17. 2020CAiRE-COVID: A Question Answering and Query-focused Multi-Document Summarization System for COVID-19 Scholarly Information Managementcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 3; 2023: 5; 2024: 3; 2025: 0; 2026: 1.

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  1. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 888
  2. 2022Read before Generate! Faithful Long Form Question Answering with Machine Readingcited by 47
  3. 2021Exploring Neural Models for Query-Focused Summarizationcited by 44
  4. 2021Domain Adaptation with Pre-trained Transformers for Query Focused Abstractive Text Summarizationcited by 21
  5. 2021AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarizationcited by 10
  6. 2023A Lightweight Constrained Generation Alternative for Query-focused Summarizationcited by 8
  7. 2022Why Do You Feel This Way? Summarizing Triggers of Emotions in Social Media Postscited by 5
  8. 2022Few-shot Query-Focused Summarization with Prefix-Mergingcited by 5
  9. 2023QontSum: On Contrasting Salient Content for Query-focused Summarizationcited by 4
  10. 2024Learning to Rank Salient Content for Query-focused Summarizationcited by 3
  11. 2023Instructive Dialogue Summarization with Query Aggregationscited by 2
  12. 2024Label-Free Topic-Focused Summarization Using Query Augmentationcited by 2
3 more
  1. 2023Generating Query Focused Summaries without Fine-tuning the Transformer-based Pre-trained Modelscited by 1
  2. 2024Does This Summary Answer My Question? Modeling Query-Focused Summary Readers with Rational Speech Actscited by 0
  3. 2026Generating Query-Focused Summarization Datasets from Query-Free Summarization Datasetscited by 0