mlsanityData to 14 Oct 2026

MAPLE: Micro Analysis of Pairwise Language Evolution for Few-Shot Claim Verification

arXiv 2401.16282 ↗First posted 29 Jan 2024cs.CL cs.AI cs.LGcited by 5

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Abstract (arXiv)

Claim verification is an essential step in the automated fact-checking pipeline which assesses the veracity of a claim against a piece of evidence. In this work, we explore the potential of few-shot claim verification, where only very limited data is available for supervision. We propose MAPLE (Micro Analysis of Pairwise Language Evolution), a pioneering approach that explores the alignment between a claim and its evidence with a small seq2seq model and a novel semantic measure. Its innovative utilization of micro language evolution path leverages unlabelled pairwise data to facilitate claim verification while imposing low demand on data annotations and computing resources. MAPLE demonstrates significant performance improvements over SOTA baselines SEED, PET and LLaMA 2 across three fact-checking datasets: FEVER, Climate FEVER, and SciFact. Data and code are available here: https://github.com/XiaZeng0223/MAPLE

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 29 of its 43 references that are in the map. First posted on arXiv 29 Jan 2024.

Builds on

29 of 43 references.

References · 29

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  5. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
  6. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,375
  7. 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,203
  8. 2020Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inferencecited by 938
  9. 2021BARTScore: Evaluating Generated Text as Text Generationcited by 722
  10. 2020It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learnerscited by 669
  11. 2020KILT: a Benchmark for Knowledge Intensive Language Taskscited by 573
  12. 2020Fact or Fiction: Verifying Scientific Claimscited by 554
17 more
  1. 2021A Survey on Automated Fact-Checkingcited by 378
  2. 2023How is ChatGPT's behavior changing over time?cited by 270
  3. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 225
  4. 2020Explainable Automated Fact-Checking for Public Health Claimscited by 211
  5. 2020CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claimscited by 196
  6. 2021Automated Fact-Checking for Assisting Human Fact-Checkerscited by 144
  7. 2020Generating Fact Checking Explanationscited by 132
  8. 2018Automated Fact Checking: Task formulations, methods and future directionscited by 96
  9. 2020Explainable Automated Fact-Checking: A Surveycited by 83
  10. 2021Towards Few-Shot Fact-Checking via Perplexitycited by 63
  11. 2021Automated Fact-Checking: A Surveycited by 55
  12. 2020Scientific Claim Verification with VERT5ERINIcited by 47
  13. 2020A Paragraph-level Multi-task Learning Model for Scientific Fact-Verificationcited by 29
  14. 2021Abstract, Rationale, Stance: A Joint Model for Scientific Claim Verificationcited by 20
  15. 2021QMUL-SDS at SCIVER: Step-by-Step Binary Classification for Scientific Claim Verificationcited by 6
  16. 2022RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verificationcited by 5
  17. 2022Active PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Trainingcited by 5

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Citing papers per year: 2024: 4; 2025: 1.

5 papers.