The authors create the first Spanish-language multi-label dataset of potentially abusive clauses in Chilean terms of service and benchmark fine-tuned and few-shot language models on it.
CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
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.
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Predicting potentially abusive clauses in Chilean terms of services with natural language processing
The authors create the first Spanish-language multi-label dataset of potentially abusive clauses in Chilean terms of service and benchmark fine-tuned and few-shot language models on it.