2 papers
cs.LG2026
A Theoretical Analysis of Mamba's Training Dynamics: Filtering Relevant Features for Generalization in State Space Models
Mugunthan Shandirasegaran, Hongkang Li, Songyang Zhang +2
The recent empirical success of Mamba and other selective state space models (SSMs) has renewed interest in non-attention architectures for sequence modeling, yet their theoretical…
cs.LG2026
Theoretical Analysis of Contrastive Learning under Imbalanced Data: From Training Dynamics to a Pruning Solution
Haixu Liao, Yating Zhou, Songyang Zhang +2
Contrastive learning has emerged as a powerful framework for learning generalizable representations, yet its theoretical understanding remains limited, particularly under imbalance…