74 citations · 112 across the 12 of their papers we have counts for
5 papers · 1 filter
Diversity Matters: Revisiting Test-Time Compute in Vision-Language Models
Yijie Tong, Yifan Hou, Shaobo Cui +2
Test-time compute (TTC) strategies have emerged as a lightweight approach to boost reasoning in large language models (LLMs). However, their application and benefits for vision-lan…
A Representation Learning Framework for Property Graphs
Yifan Hou, Hongzhi Chen, Changji Li +2
Representation learning on graphs, also called graph embedding, has demonstrated its significant impact on a series of machine learning applications such as classification, predict…
Measuring and Improving the Use of Graph Information in Graph Neural Networks
Yifan Hou, Jian Zhang, James Cheng +4
Graph neural networks (GNNs) have been widely used for representation learning on graph data. However, there is limited understanding on how much performance GNNs actually gain fro…
Understanding Graph Neural Networks from Graph Signal Denoising Perspectives
Guoji Fu, Yifan Hou, Jian Zhang +3
Graph neural networks (GNNs) have attracted much attention because of their excellent performance on tasks such as node classification. However, there is inadequate understanding o…
Context-Aware Online Learning for Course Recommendation of MOOC Big Data
Yifan Hou, Pan Zhou, Ting Wang +3
The Massive Open Online Course (MOOC) has expanded significantly in recent years. With the widespread of MOOC, the opportunity to study the fascinating courses for free has attract…