CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service
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Abstract (arXiv)
Terms of service of on-line platforms too often contain clauses that are potentially unfair to the consumer. We present an experimental study where machine learning is employed to automatically detect such potentially unfair clauses. Results show that the proposed system could provide a valuable tool for lawyers and consumers alike.
Key facts. Cited by 73 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 May 2018.
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Citing papers per year: 2021: 12; 2022: 5; 2023: 15; 2024: 17; 2025: 15; 2026: 9.
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- 2024Are LLM-based methods good enough for detecting unfair terms of service?cited by 1
50 most cited of 73 All 73 (JSON)
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- 2025Computational Identification of Regulatory Statements in EU Legislation1 May 2025
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- 2025Forget About It: Mitigating Forgetting Without Replay or Auxiliary Objectives9 Jan 2025
- 2024Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges25 Oct 2024
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- 2024Interpretable Cross-Examination Technique (ICE-T): Using highly informative features to boost LLM performance8 May 2024
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- 2024Annotation and Classification of Relevant Clauses in Terms-and-Conditions Contracts22 Feb 2024
- 2024The Right Model for the Job: An Evaluation of Legal Multi-Label Classification Baselines22 Jan 2024
- 2024Combining topic modelling and citation network analysis to study case law from the European Court on Human Rights on the right to respect for private and family life19 Jan 2024
- 2024LLaMA Pro: Progressive LLaMA with Block Expansion4 Jan 2024
- 2023Towards Mitigating Perceived Unfairness in Contracts from a Non-Legal Stakeholder's Perspective3 Dec 2023
- 2023Human Still Wins over LLM: An Empirical Study of Active Learning on Domain-Specific Annotation Tasks16 Nov 2023
- 2023An energy-based comparative analysis of common approaches to text classification in the Legal domain2 Nov 2023
- 2023Adapting Large Language Models to Domains via Reading Comprehension18 Sep 2023
- 2023NESTLE: a No-Code Tool for Statistical Analysis of Legal Corpus8 Sep 2023
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- 2023Metacognitive Prompting Improves Understanding in Large Language Models10 Aug 2023
- 2023Towards Grammatical Tagging for the Legal Language of Cybersecurity29 Jun 2023
50 newest of 73 All 73 (JSON)
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- 2021LexGLUE: A Benchmark Dataset for Legal Language Understanding in Englishcited by 310
- 2021When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Datasetcited by 201
- 2021ContractNLI: A Dataset for Document-level Natural Language Inference for Contractscited by 148
- 2022Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Datasetcited by 113
- 2024LLaMA Pro: Progressive LLaMA with Block Expansioncited by 101
- 2023MultiLegalPile: A 689GB Multilingual Legal Corpuscited by 60
- 2023Metacognitive Prompting Improves Understanding in Large Language Modelscited by 58
- 2022A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challengescited by 50
- 2023Adapting Large Language Models to Domains via Reading Comprehensioncited by 50
- 2022Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularitiescited by 47
- 2024A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Taskscited by 47
- 2021RAFT: A Real-World Few-Shot Text Classification Benchmarkcited by 44
12 most cited of 67 All 67 (JSON)
- 2026ARCCS: An Automated Regulatory Compliance Checking System1 Oct 2026
- 2026N"urnberg NLP at ChildSafeAds 2026: Structurally Dissimilar Voter Ensembles under Four Levels of Data Access28 Sep 2026
- 2026Privacy Washing: Detecting Internal Contradictions in Privacy Policies2 Sep 2026
- 2026Enabling Multilingual Privacy Policy Audits: Large-Scale Analysis of Spanish Mobile Apps20 Jul 2026
- 2026Discourse-Aware Policy Analysis with Argumentation: A Hybrid LLM-Symbolic Framework for Disaster Governance14 Jul 2026
- 2026De Jure: Iterative LLM Self-Refinement for Structured Extraction of Regulatory Rules2 Apr 2026
- 2025Text to Trust: Evaluating Fine-Tuning and LoRA Trade-offs in Language Models for Unfair Terms of Service Detection26 Oct 2025
- 2025Efficient Prompt Optimisation for Legal Text Classification with Proxy Prompt Evaluator9 Oct 2025
- 2025Exploring Selective Retrieval-Augmentation for Long-Tail Legal Text Classification27 Aug 2025
- 2025Evaluating Customized vs. Generalist Transformer-based Models for Legal Contract Classification11 Aug 2025
- 2025From Prediction to Explanation: Multimodal, Explainable, and Interactive Deepfake Detection Framework for Non-Expert Users11 Aug 2025
- 2025Demo: TOSense -- What Did You Just Agree to?1 Aug 2025
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