Unfair clause detection is an extremely useful AI application for consumer protection. Artificial intelligence has recently been successful in building systems capable to automatically detect unfair clauses in Terms of Service, and also to identify their unfairness categories. Since Large Language Models (LLMs) are nowadays bringing a revolution to the field of artificial intelligence, and in particular to natural language processing and understanding, in this paper we compare several different prompt strategies for LLMs with more traditional BERT-based fine-tuned models. Our extensive experimental evaluation aims to investigate whether it is worth using LLMs also for this challenging domain-specific task.
Panarelli, M., Galassi, A., Lagioia, F., Liepina, R., Lippi, M., Pałka, P., et al. (2026). Is It Worth Using LLMs for Unfair Clause Detection in Terms of Service?. New York : ACM- Association for Computing Machinery [10.1145/3769126.3769218].
Is It Worth Using LLMs for Unfair Clause Detection in Terms of Service?
Andrea Galassi
;Francesca Lagioia
;Ruta Liepina;Marco Lippi;Giovanni Sartor
2026
Abstract
Unfair clause detection is an extremely useful AI application for consumer protection. Artificial intelligence has recently been successful in building systems capable to automatically detect unfair clauses in Terms of Service, and also to identify their unfairness categories. Since Large Language Models (LLMs) are nowadays bringing a revolution to the field of artificial intelligence, and in particular to natural language processing and understanding, in this paper we compare several different prompt strategies for LLMs with more traditional BERT-based fine-tuned models. Our extensive experimental evaluation aims to investigate whether it is worth using LLMs also for this challenging domain-specific task.| File | Dimensione | Formato | |
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