3 papers
cs.LG2026
Model Capacity Determines Grokking through Competing Memorisation and Generalisation Speeds
Yiding Song, Hanming Ye
Existing accounts of grokking explain the phenomena in terms of mechanistic frameworks such as circuit efficiency or lazy-to-rich transitions. However, despite a known dependence b…
cs.LG2026
Non-Parametric Rehearsal Learning via Conditional Mean Embeddings
Wen-Bo Du, Tian-Zuo Wang, Han-Jia Ye +1
In machine learning, a critical class of decision-related problems concerns preventing predicted undesirable outcomes, referred to as the \textit{avoiding undesired future} (AUF) p…
cs.CV2026
Cross-Sample Relational Fusion: Unifying Domain Generalization and Class-Incremental Learning
Zhen-Hao Xie, Yan Wang, Hao Sun +3
Class-Incremental Learning (CIL) requires a learning system to learn new classes while retaining previously learned knowledge. However, in real-world scenarios such as autonomous d…