2 papers
cs.LG2026
How Do Transformers Learn to Represent Symmetries?
Eduardo Santos-Escriche, Valerie Engelmayer, Ya-Wei Eileen Lin +1
Training Transformer-based architectures with finite data augmentation has become an increasingly popular approach in geometric machine learning. Despite its empirical success, the…
cs.LG2025
Sequential-Parallel Duality in Prefix Scannable Models
Morris Yau, Sharut Gupta, Valerie Engelmayer +3
Modern neural sequence models are designed to meet the dual mandate of parallelizable training and fast sequential inference. Recent developments have given rise to various models,…