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cs.LG2026
Heterogeneous Structured Pruning Under Resource Constraints for Hardware-Efficient Large Language Models
Cameron Barker, Andreas Paraskeva, Jan N. van Rijn +2
Training-free pruning removes weights from pretrained large language models to reduce their deployment cost. However, existing approaches typically consider only the total number o…
cs.LG2026
Kalman Linear Attention: Parallel Bayesian Filtering For Efficient Language Modelling and State Tracking
Vaisakh Shaj, Cameron Barker, Aidan Scannell +3
State-space language models such as Mamba and gated linear attention (GLA) offer linear-complexity, parallelisable alternatives to transformers, but their linear state updates limi…