6 citations · 12 across the 8 of their papers we have counts for
3 papers · 1 filter
Coarse-to-Fine Open-Set Graph Node Classification with Large Language Models
Xueqi Ma, Xingjun Ma, Sarah Monazam Erfani +2
Developing open-set classification methods capable of classifying in-distribution (ID) data while detecting out-of-distribution (OOD) samples is essential for deploying graph neura…
TensorSLM: Energy-efficient Embedding Compression of Sub-billion Parameter Language Models on Low-end Devices
Mingxue Xu, Yao Lei Xu, Danilo P. Mandic
Small Language Models (SLMs, or on-device LMs) have significantly fewer parameters than Large Language Models (LLMs). They are typically deployed on low-end devices, like mobile ph…
How can representation dimension dominate structurally pruned LLMs?
Mingxue Xu, Lisa Alazraki, Danilo P. Mandic
Pruning assumes a subnetwork exists in the original deep neural network, which can achieve comparative model performance with less computation than the original. However, it is unc…