6 citations · 6 across the 10 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation
Siqing Song, Chuang Wang, Yong Lang +2
Deploying large language models (LLMs) in resource-constrained environments is hindered by heavy computational and memory requirements. We present LBLLM, a lightweight binarization…
cs.LG2026
Flux Attention: Context-Aware Hybrid Attention for Efficient LLMs Inference
Quantong Qiu, Zhiyi Hong, Yi Yang +5
The quadratic computational complexity of standard attention mechanisms presents a severe scalability bottleneck for LLMs in long-context scenarios. While hybrid attention mechanis…
cs.LG2023
DYAD: A Descriptive Yet Abjuring Density efficient approximation to linear neural network layers
Sarin Chandy, Varun Gangal, Yi Yang +1
We devise, implement and performance-asses DYAD, a layer which can serve as a faster and more memory-efficient approximate replacement for linear layers, (nn.Linear() in Pytorch).…