mlsanityData to 14 Oct 2026

Explaining Veracity Predictions with Evidence Summarization: A Multi-Task Model Approach

arXiv 2402.06443 ↗First posted 9 Feb 2024cs.CLcited by 4

Not on the map. Why?

Abstract (arXiv)

The rapid dissemination of misinformation through social media increased the importance of automated fact-checking. Furthermore, studies on what deep neural models pay attention to when making predictions have increased in recent years. While significant progress has been made in this field, it has not yet reached a level of reasoning comparable to human reasoning. To address these gaps, we propose a multi-task explainable neural model for misinformation detection. Specifically, this work formulates an explanation generation process of the model's veracity prediction as a text summarization problem. Additionally, the performance of the proposed model is discussed on publicly available datasets and the findings are evaluated with related studies.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 37 of its 69 references that are in the map. First posted on arXiv 9 Feb 2024.

Builds on

37 of 69 references.

References · 37

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  5. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  6. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  7. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  8. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,307
  9. 2022Scaling Instruction-Finetuned Language Modelscited by 3,024
  10. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,375
  11. 2017Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semanticscited by 1,358
  12. 2017A Survey on Multi-Task Learningcited by 840
25 more
  1. 2021A Survey on Automated Fact-Checkingcited by 378
  2. 2020Multi-Task Learning with Deep Neural Networks: A Surveycited by 375
  3. 2017Fake News Detection on Social Media: A Data Mining Perspectivecited by 336
  4. 2020Explainable Automated Fact-Checking for Public Health Claimscited by 211
  5. 2023Fact-Checking Complex Claims with Program-Guided Reasoningcited by 146
  6. 2017Automatic Detection of Fake Newscited by 145
  7. 2020Generating Fact Checking Explanationscited by 132
  8. 2020GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Mediacited by 109
  9. 2018DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learningcited by 100
  10. 2020Explainable Automated Fact-Checking: A Surveycited by 83
  11. 2018A Survey on Natural Language Processing for Fake News Detectioncited by 67
  12. 2021Multi-Task Learning in Natural Language Processing: An Overviewcited by 62
  13. 2023Scientific Fact-Checking: A Survey of Resources and Approachescited by 54
  14. 2019Network-based Fake News Detection: A Pattern-driven Approachcited by 33
  15. 2019Fake News Early Detection: An Interdisciplinary Studycited by 29
  16. 2024JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claimscited by 29
  17. 2020Generating Label Cohesive and Well-Formed Adversarial Claimscited by 27
  18. 2020Causal Understanding of Fake News Dissemination on Social Mediacited by 27
  19. 2022Varifocal Question Generation for Fact-checkingcited by 27
  20. 2021Explainable Fact-checking through Question Answeringcited by 16
  21. 2019Credibility-based Fake News Detectioncited by 11
  22. 2022Ask to Know More: Generating Counterfactual Explanations for Fake Claimscited by 8
  23. 2021Exploring Multitask Learning for Low-Resource AbstractiveSummarizationcited by 5
  24. 2024Automated Fact-Checking of Climate Change Claims with Large Language Modelscited by 4
  25. 2019Mapping (Dis-)Information Flow about the MH17 Plane Crashcited by 3

Built on by

Cited by year

Citing papers per year: 2024: 3; 2025: 1.

4 papers.

  1. 2024Generative Large Language Models in Automated Fact-Checking: A Surveycited by 19
  2. 2024Cross-Lingual Learning vs. Low-Resource Fine-Tuning: A Case Study with Fact-Checking in Turkishcited by 4
  3. 2024Generative Debunking of Climate Misinformationcited by 1
  4. 2025CANDY: Benchmarking LLMs' Limitations and Assistive Potential in Chinese Misinformation Fact-Checkingcited by 1