mlsanityData to 7 Oct 2026

Claim Matching Beyond English to Scale Global Fact-Checking

arXiv 2106.00853 ↗First posted 1 Jun 2021cs.CLcited by 42

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Abstract (arXiv)

Manual fact-checking does not scale well to serve the needs of the internet. This issue is further compounded in non-English contexts. In this paper, we discuss claim matching as a possible solution to scale fact-checking. We define claim matching as the task of identifying pairs of textual messages containing claims that can be served with one fact-check. We construct a novel dataset of WhatsApp tipline and public group messages alongside fact-checked claims that are first annotated for containing "claim-like statements" and then matched with potentially similar items and annotated for claim matching. Our dataset contains content in high-resource (English, Hindi) and lower-resource (Bengali, Malayalam, Tamil) languages. We train our own embedding model using knowledge distillation and a high-quality "teacher" model in order to address the imbalance in embedding quality between the low- and high-resource languages in our dataset. We provide evaluations on the performance of our solution and compare with baselines and existing state-of-the-art multilingual embedding models, namely LASER and LaBSE. We demonstrate that our performance exceeds LASER and LaBSE in all settings. We release our annotated datasets, codebooks, and trained embedding model to allow for further research.

Key facts. Cited by 42 papers in the map (data through 7 Oct 2026). Builds on 17 of its 40 references that are in the map. First posted on arXiv 1 Jun 2021.

Builds on

17 of 40 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  4. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  5. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
  6. 2017SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluationcited by 998
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  8. 2020Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillationcited by 591
  9. 2018Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyondcited by 434
  10. 2019Multilingual and Multi-Aspect Hate Speech Analysiscited by 133
  11. 2020That is a Known Lie: Detecting Previously Fact-Checked Claimscited by 82
  12. 2019Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmaxcited by 58
5 more
  1. 2018Towards Automated Factchecking: Developing an Annotation Schema and Benchmark for Consistent Automated Claim Detectioncited by 55
  2. 2020Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake Newscited by 48
  3. 2020CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Mediacited by 25
  4. 2020Images and Misinformation in Political Groups: Evidence from WhatsApp in Indiacited by 11
  5. 2020Text Similarity Using Word Embeddings to Classify Misinformationcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 5; 2023: 8; 2024: 6; 2025: 15; 2026: 3.

42 papers.

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  1. 2021A Survey on Automated Fact-Checkingcited by 376
  2. 2023AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Webcited by 144
  3. 2024Claim Detection for Automated Fact-checking: A Survey on Monolingual, Multilingual and Cross-Lingual Researchcited by 35
  4. 2023Multilingual Previously Fact-Checked Claim Retrievalcited by 32
  5. 2023Factify 2: A Multimodal Fake News and Satire News Datasetcited by 23
  6. 2024PROXYQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Modelscited by 23
  7. 2021Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Documentcited by 19
  8. 2022Matching Tweets With Applicable Fact-Checks Across Languagescited by 15
  9. 2022CONCRETE: Improving Cross-lingual Fact-checking with Cross-lingual Retrievalcited by 14
  10. 2025Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checkingcited by 12
  11. 2021Dataset of Fake News Detection and Fact Verification: A Surveycited by 11
  12. 2025SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrievalcited by 11
30 more
  1. 2023Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AIcited by 9
  2. 2022Autonomation, Not Automation: Activities and Needs of European Fact-checkers as a Basis for Designing Human-Centered AI Systemscited by 7
  3. 2023Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Modelscited by 7
  4. 2025MultiClaimNet: A Massively Multilingual Dataset of Fact-Checked Claim Clusterscited by 7
  5. 2022CsFEVER and CTKFacts: Acquiring Czech data for fact verificationcited by 6
  6. 2025Large Language Models for Multilingual Previously Fact-Checked Claim Detectioncited by 6
  7. 2023Breaking Language Barriers with MMTweets: Advancing Cross-Lingual Debunked Narrative Retrieval for Fact-Checkingcited by 5
  8. 2024Cross-Lingual Learning vs. Low-Resource Fine-Tuning: A Case Study with Fact-Checking in Turkishcited by 4
  9. 2024A Survey on Automatic Credibility Assessment Using Textual Credibility Signals in the Era of Large Language Modelscited by 3
  10. 2025When Claims Evolve: Evaluating and Enhancing the Robustness of Embedding Models Against Misinformation Editscited by 3
  11. 2025Entity-aware Cross-lingual Claim Detection for Automated Fact-checkingcited by 3
  12. 2025ViClaim: A Multilingual Multilabel Dataset for Automatic Claim Detection in Videoscited by 3
  13. 2021Tiplines to Combat Misinformation on Encrypted Platforms: A Case Study of the 2019 Indian Election on WhatsAppcited by 2
  14. 2022Query Rewriting for Effective Misinformation Discoverycited by 2
  15. 2024SynDy: Synthetic Dynamic Dataset Generation Framework for Misinformation Taskscited by 2
  16. 2023Low-Shot Learning for Fictional Claim Verificationcited by 1
  17. 2023Lost in translation: using global fact-checks to measure multilingual misinformation prevalence, spread, and evolutioncited by 1
  18. 2024Synergizing Machine Learning & Symbolic Methods: A Survey on Hybrid Approaches to Natural Language Processingcited by 1
  19. 2025Word2winners at SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrievalcited by 1
  20. 2025A Generative-AI-Driven Claim Retrieval System Capable of Detecting and Retrieving Claims from Social Media Platforms in Multiple Languagescited by 1
  21. 2025Multilingual vs Crosslingual Retrieval of Fact-Checked Claims: A Tale of Two Approachescited by 1
  22. 2025The Psychology of Falsehood: A Human-Centric Survey of Misinformation Detectioncited by 1
  23. 2025Investigating Language and Retrieval Bias in Multilingual Previously Fact-Checked Claim Detectioncited by 1
  24. 2021Logically at Factify 2022: Multimodal Fact Verificationcited by 0
  25. 2025o-MEGA: Optimized Methods for Explanation Generation and Analysiscited by 0
  26. 2025Agent-based Automated Claim Matching with Instruction-following LLMscited by 0
  27. 2025MultiMind at SemEval-2025 Task 7: Crosslingual Fact-Checked Claim Retrieval via Multi-Source Alignmentcited by 0
  28. 2026Claim2Vec: Embedding Fact-Check Claims for Multilingual Similarity and Clusteringcited by 0
  29. 2026Language Mutations Sustain the Persistences of Conspiracy Theories on Social Mediacited by 0
  30. 2026Multilingual and Cross-Lingual Citation Needed Detection on Wikipedia for Lower-Resource Languagescited by 0