25 citations · 33 across the 15 of their papers we have counts for
14 papers · 1 filter
Elucidating the Design Space of Decay in Linear Attention
Zhen Qin, Xuyang Shen, Yiran Zhong
This paper presents a comprehensive investigation into the decay mechanisms inherent in linear complexity sequence models. We systematically delineate the design space of decay mec…
Scaling Laws for Linear Complexity Language Models
Xuyang Shen, Dong Li, Ruitao Leng +3
The interest in linear complexity models for large language models is on the rise, although their scaling capacity remains uncertain. In this study, we present the scaling laws for…
Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention
Zhen Qin, Weigao Sun, Dong Li +3
We present Lightning Attention, the first linear attention implementation that maintains a constant training speed for various sequence lengths under fixed memory consumption. Due…
You Only Scan Once: Efficient Multi-dimension Sequential Modeling with LightNet
Zhen Qin, Yuxin Mao, Xuyang Shen +4
Linear attention mechanisms have gained prominence in causal language models due to their linear computational complexity and enhanced speed. However, the inherent decay mechanism…
Unlocking the Secrets of Linear Complexity Sequence Model from A Unified Perspective
Zhen Qin, Xuyang Shen, Dong Li +4
We present the Linear Complexity Sequence Model (LCSM), a comprehensive solution that unites various sequence modeling techniques with linear complexity, including linear attention…
HGRN2: Gated Linear RNNs with State Expansion
Zhen Qin, Songlin Yang, Weixuan Sun +4
Hierarchically gated linear RNN (HGRN, \citealt{HGRN}) has demonstrated competitive training speed and performance in language modeling while offering efficient inference. However,…