no code implementations • 23 Oct 2024 • Jingfan Zhang, Yi Zhao, Dan Chen, Xing Tian, Huanran Zheng, Wei Zhu
Low-rank adaptation (LoRA) and its mixture-of-experts (MOE) variants are highly effective parameter-efficient fine-tuning (PEFT) methods.
no code implementations • 24 Mar 2024 • Zequan Liu, Jiawen Lyn, Wei Zhu, Xing Tian, Yvette Graham
Parameter-efficient fine-tuning (PEFT) is widely studied for its effectiveness and efficiency in the era of large language models.
1 code implementation • 4 Jan 2024 • Wei Zhu, Wenfeng Li, Xing Tian, Pengfei Wang, Xiaoling Wang, Jin Chen, Yuanbin Wu, Yuan Ni, Guotong Xie
In this work, we propose a novel task, Text2MDT, to explore the automatic extraction of MDTs from medical texts such as medical guidelines and textbooks.
1 code implementation • 13 Jul 2021 • Jiajie Zou, Yuran Zhang, Jialu Li, Xing Tian, Nai Ding
Furthermore, when readers scan a passage without a question in mind, their reading time is predicted by DNNs optimized for a word prediction task.
1 code implementation • 29 Jun 2020 • Wing WY Ng, Shichao Xu, Jianjun Zhang, Xing Tian, Tongwen Rong, Sam Kwong
Samples in the majority class are divided into many subspaces by a hashing method.
no code implementations • 29 Jun 2020 • Shengfei Lyu, Xing Tian, Yang Li, Bingbing Jiang, Huanhuan Chen
The probabilistic classification vector machine (PCVM) synthesizes the advantages of both the support vector machine and the relevant vector machine, delivering a sparse Bayesian solution to classification problems.