ERASE

ERASE is a large-scale benchmark for machine unlearning in recommender systems that evaluates three core tasks—collaborative filtering, session-based recommendation, and next-basket recommendation—while incorporating real-world unlearning scenarios and covering multiple unlearning algorithms and datasets.

Papers using ERASE (1)

ERASE -- A Real-World Aligned Benchmark for Unlearning in Recommender Systems2026