# CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service

arXiv: https://arxiv.org/abs/1805.01217 · HTML: https://mlsanity.com/paper/1805.01217/

## Key facts

- Cited by 73 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 May 2018.

## Built on by (most cited first, 30 of 73)

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- [Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges](https://mlsanity.com/paper/2410.21306/) (2024)
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- [ChatGPT may Pass the Bar Exam soon, but has a Long Way to Go for the LexGLUE benchmark](https://mlsanity.com/paper/2304.12202/) (2023)
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- [Bringing order into the realm of Transformer-based language models for artificial intelligence and law](https://mlsanity.com/paper/2308.05502/) (2023)
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- [ChronosLex: Time-aware Incremental Training for Temporal Generalization of Legal Classification Tasks](https://mlsanity.com/paper/2405.14211/) (2024)
- [LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain](https://mlsanity.com/paper/2404.02127/) (2024)
- [Automated Few-shot Classification with Instruction-Finetuned Language Models](https://mlsanity.com/paper/2305.12576/) (2023)
- [LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in English](https://mlsanity.com/paper/2410.09527/) (2024)
- [AI-enabled Automation for Completeness Checking of Privacy Policies](https://mlsanity.com/paper/2106.05688/) (2021)
- [DPPA: Pruning Method for Large Language Model to Model Merging](https://mlsanity.com/paper/2403.02799/) (2024)
- [Lawma: The Power of Specialization for Legal Annotation](https://mlsanity.com/paper/2407.16615/) (2024)
- [Llama SLayer 8B: Shallow Layers Hold the Key to Knowledge Injection](https://mlsanity.com/paper/2410.02330/) (2024)
- [A Survey of Classification Tasks and Approaches for Legal Contracts](https://mlsanity.com/paper/2507.21108/) (2025)

## 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.