3 papers
cs.LG2026
Retrieval-Augmented Detection of Potentially Abusive Clauses in Chilean Terms of Service
Christoffer Loeffler, Tomás Rey Pizarro, Daniel Ignacio Miranda Vásquez +1
Online Terms of Service often function as contracts of adhesion, creating asymmetries that may expose consumers to potentially abusive clauses. In Chile, assessing such clauses is…
cs.LG2025
Effective Data Pruning through Score Extrapolation
Sebastian Schmidt, Prasanga Dhungel, Christoffer Löffler +3
Training advanced machine learning models demands massive datasets, resulting in prohibitive computational costs. To address this challenge, data pruning techniques identify and re…
cs.CL2025
Predicting potentially abusive clauses in Chilean terms of services with natural language processing
Christoffer Loeffler, Andrea Martínez Freile, Tomás Rey Pizarro
This study addresses the growing concern of information asymmetry in consumer contracts, exacerbated by the proliferation of online services with complex Terms of Service that are…