43 citations · 124 across the 14 of their papers we have counts for
4 papers · 1 filter
What Makes for Robust Multi-Modal Models in the Face of Missing Modalities?
Siting Li, Chenzhuang Du, Yue Zhao +2
With the growing success of multi-modal learning, research on the robustness of multi-modal models, especially when facing situations with missing modalities, is receiving increase…
Improving Discriminative Multi-Modal Learning with Large-Scale Pre-Trained Models
Chenzhuang Du, Yue Zhao, Chonghua Liao +3
This paper investigates how to better leverage large-scale pre-trained uni-modal models to further enhance discriminative multi-modal learning. Even when fine-tuned with only uni-m…
On Uni-Modal Feature Learning in Supervised Multi-Modal Learning
Chenzhuang Du, Jiaye Teng, Tingle Li +5
We abstract the features (i.e. learned representations) of multi-modal data into 1) uni-modal features, which can be learned from uni-modal training, and 2) paired features, which…
ChatDB: Augmenting LLMs with Databases as Their Symbolic Memory
Chenxu Hu, Jie Fu, Chenzhuang Du +3
Large language models (LLMs) with memory are computationally universal. However, mainstream LLMs are not taking full advantage of memory, and the designs are heavily influenced by…