3 citations · 5 across the 4 of their papers we have counts for
4 papers
GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning
Kaiyuan Tian, Yu Tang, Gongqingjian Jiang +5
Full-parameter fine-tuning of large language models is constrained by substantial GPU memory requirements. Low-rank adaptation methods mitigate this challenge by updating only a su…
A Survey on Memory-Efficient Transformer-Based Model Training in AI for Science
Kaiyuan Tian, Linbo Qiao, Baihui Liu +3
Scientific research faces high costs and inefficiencies with traditional methods, but the rise of deep learning and large language models (LLMs) offers innovative solutions. This s…
Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models
Yifu Gao, Linbo Qiao, Zhigang Kan +3
Temporal knowledge graph question answering (TKGQA) poses a significant challenge task, due to the temporal constraints hidden in questions and the answers sought from dynamic stru…
TFDMNet: A Novel Network Structure Combines the Time Domain and Frequency Domain Features
Hengyue Pan, Yixin Chen, Zhiliang Tian +3
Convolutional neural network (CNN) has achieved impressive success in computer vision during the past few decades. The image convolution operation helps CNNs to get good performanc…