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cs.LG2026
LampAttention: Look-Ahead Mixed-Precision FlashAttention for Dedicated Accelerators
Stanislav Budzinskiy, Marian Gloser, Tolunay Yilmaz +5
While most attention logits can be computed in low precision without degrading numerical stability, current attention kernels fail to exploit this phenomenon. We introduce a novel…
cs.LG2026
Dispelling the Curse of Singularities in Neural Network Optimizations
Hengjie Cao, Mengyi Chen, Yifeng Yang +11
This work investigates the optimization instability of deep neural networks from a less-explored yet insightful perspective: the emergence and amplification of singularities in the…
cs.LG2026
LAMP: Look-Ahead Mixed-Precision Inference of Large Language Models
Stanislav Budzinskiy, Marian Gloser, Tolunay Yilmaz +5
Mixed-precision computations are a hallmark of the current stage of AI, driving the progress in large language models towards efficient, locally deployable solutions. This article…