Paper recorded by Signals 4 on 2026-11-01 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-11-01 on arXiv · recorded by Signals 4 on 2026-11-03
Category: cs.LG · 机器学习 · first seen 2026-11-03
Linear recurrences are becoming an increasingly common building block in large language models, replacing the growing KV cache of softmax attention with a fixed-size recurrent state that enables efficient decoding. However, the quantization stack has largely been developed around softmax Transformers, whose numerical properties and inference state differ from those of recurrent models. Our goal is