38 citations · 53 across the 12 of their papers we have counts for
4 papers · 1 filter
From Efficient Multimodal Models to World Models: A Survey
Xinji Mai, Zeng Tao, Junxiong Lin +5
Multimodal Large Models (MLMs) are becoming a significant research focus, combining powerful large language models with multimodal learning to perform complex tasks across differen…
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs
Pengfei Ding, Yan Wang, Guanfeng Liu +2
Heterogeneous graph few-shot learning (HGFL) has been developed to address the label sparsity issue in heterogeneous graphs (HGs), which consist of various types of nodes and edges…
Explainable History Distillation by Marked Temporal Point Process
Sishun Liu, Ke Deng, Yan Wang +1
Explainability of machine learning models is mandatory when researchers introduce these commonly believed black boxes to real-world tasks, especially high-stakes ones. In this pape…
e-Distance Weighted Support Vector Regression
Yan Wang, Ge Ou, Wei Pang +2
We propose a novel support vector regression approach called e-Distance Weighted Support Vector Regression (e-DWSVR).e-DWSVR specifically addresses two challenging issues in suppor…