mlsanityData to 7 Oct 2026

WiCE: Real-World Entailment for Claims in Wikipedia

arXiv 2303.01432 ↗First posted 2 Mar 2023cs.CLcited by 118

Not on the map. Why?

Abstract (arXiv)

Textual entailment models are increasingly applied in settings like fact-checking, presupposition verification in question answering, or summary evaluation. However, these represent a significant domain shift from existing entailment datasets, and models underperform as a result. We propose WiCE, a new fine-grained textual entailment dataset built on natural claim and evidence pairs extracted from Wikipedia. In addition to standard claim-level entailment, WiCE provides entailment judgments over sub-sentence units of the claim, and a minimal subset of evidence sentences that support each subclaim. To support this, we propose an automatic claim decomposition strategy using GPT-3.5 which we show is also effective at improving entailment models' performance on multiple datasets at test time. Finally, we show that real claims in our dataset involve challenging verification and retrieval problems that existing models fail to address.

Key facts. Cited by 118 papers in the map (data through 7 Oct 2026). Builds on 45 of its 66 references that are in the map. First posted on arXiv 2 Mar 2023.

Builds on

45 of 66 references.

References · 45

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2022Training language models to follow instructions with human feedbackcited by 15,712
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  5. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  6. 2020Longformer: The Long-Document Transformercited by 3,362
  7. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
  8. 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,665
  9. 2015A large annotated corpus for learning natural language inferencecited by 1,837
  10. 2018Datasheets for Datasetscited by 1,371
  11. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
  12. 2019Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inferencecited by 864
33 more
  1. 2019Adversarial NLI: A New Benchmark for Natural Language Understandingcited by 798
  2. 2018Annotation Artifacts in Natural Language Inference Datacited by 656
  3. 2021SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarizationcited by 402
  4. 2019PAWS: Paraphrase Adversaries from Word Scramblingcited by 395
  5. 2020Asking and Answering Questions to Evaluate the Factual Consistency of Summariescited by 376
  6. 2020FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarizationcited by 292
  7. 2018Hypothesis Only Baselines in Natural Language Inferencecited by 291
  8. 2022RARR: Researching and Revising What Language Models Say, Using Language Modelscited by 286
  9. 2021Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metricscited by 285
  10. 2021Measuring Attribution in Natural Language Generation Modelscited by 253
  11. 2021QuestEval: Summarization Asks for Fact-based Evaluationcited by 241
  12. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 222
  13. 2022WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creationcited by 200
  14. 2021ContractNLI: A Dataset for Document-level Natural Language Inference for Contractscited by 145
  15. 2022Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluationcited by 141
  16. 2021Annotating and Modeling Fine-grained Factuality in Summarizationcited by 131
  17. 2021Q2: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answeringcited by 131
  18. 2020Evaluating Factuality in Generation with Dependency-level Entailmentcited by 122
  19. 2018Combining Fact Extraction and Verification with Neural Semantic Matching Networkscited by 120
  20. 2021Decontextualization: Making Sentences Stand-Alonecited by 101
  21. 2019GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verificationcited by 100
  22. 2021Competency Problems: On Finding and Removing Artifacts in Language Datacited by 91
  23. 2021Evaluating Attribution in Dialogue Systems: The BEGIN Benchmarkcited by 75
  24. 2021DocNLI: A Large-scale Dataset for Document-level Natural Language Inferencecited by 75
  25. 2021DialFact: A Benchmark for Fact-Checking in Dialoguecited by 62
  26. 2021Can NLI Models Verify QA Systems' Predictions?cited by 46
  27. 2022Stretching Sentence-pair NLI Models to Reason over Long Documents and Clusterscited by 44
  28. 2021Finding a Balanced Degree of Automation for Summary Evaluationcited by 43
  29. 2019Crowdsourcing Lightweight Pyramids for Manual Summary Evaluationcited by 39
  30. 2022PropSegmEnt: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment Recognitioncited by 29
  31. 2020Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baselinecited by 22
  32. 2020LOREN: Logic-Regularized Reasoning for Interpretable Fact Verificationcited by 16
  33. 2022Shortcomings of Question Answering Based Factuality Frameworks for Error Localizationcited by 15

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 23; 2024: 44; 2025: 27; 2026: 24.

118 papers.

Sort:

By area:

  1. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,259
  2. 2023Enabling Large Language Models to Generate Text with Citationscited by 584
  3. 2023RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Modelscited by 272
  4. 2024MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documentscited by 251
  5. 2023FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarioscited by 247
  6. 2024HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughlycited by 119
  7. 2024VERISCORE: Evaluating the factuality of verifiable claims in long-form text generationcited by 114
  8. 2023Complex Claim Verification with Evidence Retrieved in the Wildcited by 110
  9. 2023R-Tuning: Instructing Large Language Models to Say `I Don't Know'cited by 106
  10. 2023ExpertQA: Expert-Curated Questions and Attributed Answerscited by 96
  11. 2023Dense X Retrieval: What Retrieval Granularity Should We Use?cited by 88
  12. 2024CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklistscited by 87
38 more
  1. 2023Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkerscited by 86
  2. 2023A Survey of Large Language Models Attributioncited by 71
  3. 2023Automatic Evaluation of Attribution by Large Language Modelscited by 70
  4. 2023FELM: Benchmarking Factuality Evaluation of Large Language Modelscited by 66
  5. 2023Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrongcited by 51
  6. 2024Evaluating LLMs at Detecting Errors in LLM Responsescited by 49
  7. 2023Understanding Retrieval Augmentation for Long-Form Question Answeringcited by 45
  8. 2024Molecular Facts: Desiderata for Decontextualization in LLM Fact Verificationcited by 42
  9. 2024A Closer Look at Claim Decompositioncited by 40
  10. 2024Decomposition Dilemmas: Does Claim Decomposition Boost or Burden Fact-Checking Performance?cited by 34
  11. 2023Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Modelscited by 31
  12. 2024K-QA: A Real-World Medical Q&A Benchmarkcited by 30
  13. 2024Fine-Grained Natural Language Inference Based Faithfulness Evaluation for Diverse Summarisation Taskscited by 23
  14. 2024Claim Verification in the Age of Large Language Models: A Surveycited by 23
  15. 2024QuanTemp: A real-world open-domain benchmark for fact-checking numerical claimscited by 22
  16. 2024DnDScore: Decontextualization and Decomposition for Factuality Verification in Long-Form Text Generationcited by 22
  17. 2024Atomic Fact Decomposition Helps Attributed Question Answeringcited by 21
  18. 2023Sub-Sentence Encoder: Contrastive Learning of Propositional Semantic Representationscited by 19
  19. 2024Generative Large Language Models in Automated Fact-Checking: A Surveycited by 19
  20. 2024FinDVer: Explainable Claim Verification over Long and Hybrid-Content Financial Documentscited by 19
  21. 2024FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answeringcited by 18
  22. 2025Towards Effective Extraction and Evaluation of Factual Claimscited by 18
  23. 2024Lived Experience Not Found: LLMs Struggle to Align with Experts on Addressing Adverse Drug Reactions from Psychiatric Medication Usecited by 17
  24. 2023Atomic Inference for NLI with Generated Facts as Atomscited by 16
  25. 2023DocLens: Multi-aspect Fine-grained Evaluation for Medical Text Generationcited by 16
  26. 2025SciVer: Evaluating Foundation Models for Multimodal Scientific Claim Verificationcited by 16
  27. 2024Verifiable Generation with Subsentence-Level Fine-Grained Citationscited by 15
  28. 2024Core: Robust Factual Precision with Informative Sub-Claim Identificationcited by 15
  29. 2023How Well Do Large Language Models Truly Ground?cited by 14
  30. 2024Halu-J: Critique-Based Hallucination Judgecited by 14
  31. 2025FactCG: Enhancing Fact Checkers with Graph-Based Multi-Hop Datacited by 14
  32. 2024PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysiscited by 13
  33. 2024Localizing Factual Inconsistencies in Attributable Text Generationcited by 13
  34. 2025Verifying the Verifiers: Unveiling Pitfalls and Potentials in Fact Verifierscited by 12
  35. 2025Behavioral Analysis of Information Salience in Large Language Modelscited by 11
  36. 2025Lost in the Maze: Overcoming Context Limitations in Long-Horizon Agentic Searchcited by 11
  37. 2023AutoHall: Automated Factuality Hallucination Dataset Generation for Large Language Modelscited by 10
  38. 2024GenAudit: Fixing Factual Errors in Language Model Outputs with Evidencecited by 10

50 most cited of 118 All 118 (JSON)