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All-in-one: Multi-task Learning for Rumour Verification

arXiv 1806.03713 ↗First posted 10 Jun 2018cs.CLcited by 54

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Abstract (arXiv)

Automatic resolution of rumours is a challenging task that can be broken down into smaller components that make up a pipeline, including rumour detection, rumour tracking and stance classification, leading to the final outcome of determining the veracity of a rumour. In previous work, these steps in the process of rumour verification have been developed as separate components where the output of one feeds into the next. We propose a multi-task learning approach that allows joint training of the main and auxiliary tasks, improving the performance of rumour verification. We examine the connection between the dataset properties and the outcomes of the multi-task learning models used.

Key facts. Cited by 54 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Jun 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 17; 2022: 12; 2023: 7; 2024: 8; 2025: 3; 2026: 7.

54 papers.

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  1. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  2. 2021Multi-Task Learning in Natural Language Processing: An Overviewcited by 61
  3. 2022MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Datasetcited by 59
  4. 2021Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multi-modal Datacited by 50
  5. 2021Towards Propagation Uncertainty: Edge-enhanced Bayesian Graph Convolutional Networks for Rumor Detectioncited by 34
  6. 2022Zoom Out and Observe: News Environment Perception for Fake News Detectioncited by 34
  7. 2021The Surprising Performance of Simple Baselines for Misinformation Detectioncited by 27
  8. 2021Integrating Pattern- and Fact-based Fake News Detection via Model Preference Learningcited by 25
  9. 2021A Survey on Predicting the Factuality and the Bias of News Mediacited by 20
  10. 2023Learn over Past, Evolve for Future: Forecasting Temporal Trends for Fake News Detectioncited by 20
  11. 2023Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classificationcited by 16
  12. 2021Let-Mi: An Arabic Levantine Twitter Dataset for Misogynistic Languagecited by 15
38 more
  1. 2024RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning Based on Emotional Informationcited by 14
  2. 2022Perturbations in the Wild: Leveraging Human-Written Text Perturbations for Realistic Adversarial Attack and Defensecited by 12
  3. 2021Dataset of Fake News Detection and Fact Verification: A Surveycited by 11
  4. 2021On Unifying Misinformation Detectioncited by 10
  5. 2022A Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learningcited by 10
  6. 2023Robust Domain Misinformation Detection via Multi-modal Feature Alignmentcited by 10
  7. 2024TELLER: A Trustworthy Framework for Explainable, Generalizable and Controllable Fake News Detectioncited by 10
  8. 2021VRoC: Variational Autoencoder-aided Multi-task Rumor Classifier Based on Textcited by 9
  9. 2021SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checkingcited by 8
  10. 2022Stanceosaurus: Classifying Stance Towards Multilingual Misinformationcited by 8
  11. 2022Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarkscited by 7
  12. 2023CRYPTEXT: Database and Interactive Toolkit of Human-Written Text Perturbations in the Wildcited by 6
  13. 2021Rumour Detection via Zero-shot Cross-lingual Transfer Learningcited by 5
  14. 2024Reinforcement Tuning for Detecting Stances and Debunking Rumors Jointly with Large Language Modelscited by 5
  15. 2021Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directionscited by 4
  16. 2024MAGPIE: Multi-Task Media-Bias Analysis Generalization for Pre-Trained Identification of Expressionscited by 4
  17. 2021Dynamically Addressing Unseen Rumor via Continual Learningcited by 3
  18. 2021Multi-View Active Learning for Short Text Classification in User-Generated Datacited by 3
  19. 2022Polarity and Subjectivity Detection with Multitask Learning and BERT Embeddingcited by 3
  20. 2022Evaluating BERT-based Pre-training Language Models for Detecting Misinformationcited by 2
  21. 2022ClaimDiff: Comparing and Contrasting Claims on Contentious Issuescited by 2
  22. 2023Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modellingcited by 2
  23. 2024Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource Limitationscited by 2
  24. 2024DIVERSE: A Dataset of YouTube Video Comment Stances with a Data Programming Modelcited by 2
  25. 2025Rumor Detection by Multi-task Suffix Learning based on Time-series Dual Sentimentscited by 2
  26. 2026Beyond the "Truth": Investigating Election Rumors on Truth Social During the 2024 Electioncited by 2
  27. 2026Data-centric Prompt Tuning for Dynamic Graphscited by 2
  28. 2022Exploring Graph-aware Multi-View Fusion for Rumor Detection on Social Mediacited by 1
  29. 2022Rumour detection using graph neural network and oversampling in benchmark Twitter datasetcited by 1
  30. 2023Bike Frames: Understanding the Implicit Portrayal of Cyclists in the Newscited by 1
  31. 2023Detecting Rumor Veracity with Only Textual Information by Double-Channel Structurecited by 1
  32. 2024Generating Zero-shot Abstractive Explanations for Rumour Verificationcited by 1
  33. 2024CMA-R:Causal Mediation Analysis for Explaining Rumour Detectioncited by 1
  34. 2026One LLM to Train Them All: Multi-Task Learning Framework for Fact-Checkingcited by 1
  35. 2026Reliable News or Propagandist News? A Neurosymbolic Model Using Genre, Topic, and Persuasion Techniques to Improve Robustness in Classificationcited by 1
  36. 2021Leveraging Commonsense Knowledge on Classifying False News and Determining Checkworthiness of Claimscited by 0
  37. 2022An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learningcited by 0
  38. 2025An Analytical Emotion Framework of Rumour Threads on Social Mediacited by 0

50 most cited of 54 All 54 (JSON)