74 citations · 108 across the 6 of their papers we have counts for
6 papers
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community
Qingyao Ai, Ting Bai, Zhao Cao +30
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Mod…
BrainNPT: Pre-training of Transformer networks for brain network classification
Jinlong Hu, Yangmin Huang, Nan Wang +1
Deep learning methods have advanced quickly in brain imaging analysis over the past few years, but they are usually restricted by the limited labeled data. Pre-trained model on unl…
Transformer and Snowball Graph Convolution Learning for Brain functional network Classification
Jinlong Hu, Yangmin Huang, Shoubin Dong
Advanced deep learning methods, especially graph neural networks (GNNs), are increasingly expected to learn from brain functional network data and predict brain disorders. In this…
A Multi-modal Fusion Framework Based on Multi-task Correlation Learning for Cancer Prognosis Prediction
Kaiwen Tan, Weixian Huang, Xiaofeng Liu +2
Morphological attributes from histopathological images and molecular profiles from genomic data are important information to drive diagnosis, prognosis, and therapy of cancers. By…
AEFE: Automatic Embedded Feature Engineering for Categorical Features
Zhenyuan Zhong, Jie Yang, Yacong Ma +2
The challenge of solving data mining problems in e-commerce applications such as recommendation system (RS) and click-through rate (CTR) prediction is how to make inferences by con…
Top-N-Rank: A Scalable List-wise Ranking Method for Recommender Systems
Junjie Liang, Jinlong Hu, Shoubin Dong +1
We propose Top-N-Rank, a novel family of list-wise Learning-to-Rank models for reliably recommending the N top-ranked items. The proposed models optimize a variant of the widely us…