3 papers
cs.LG2026
Trajectory-Guided Forget-Recover Network for Continual LLM Unlearning
Zezheng Wu, Xinghe Cheng, Qinggang Zhang +4
Machine unlearning aims to eliminate the influence of sensitive data on a model. In the real world, unlearning requests arrive continually, which gives rise to two challenges. Firs…
cs.IR2026
UniER: A Unified Benchmark for Item-level and Path-level Exercise Recommendation
Xinghe Cheng, Guiyong Zhuang, Yusheng Xie +5
Personalized exercise recommendation dynamically aligns pedagogical resources with individual knowledge mastery, which is crucial for satisfying students' dynamic learning needs in…
cs.LG2026
BamaER: A Behavior-Aware Memory-Augmented Model for Exercise Recommendation
Qing Yang, Yuhao Jiang, Rui Wang +6
Exercise recommendation focuses on personalized exercise selection conditioned on students' learning history, personal interests, and other individualized characteristics. Despite…