2 citations · 2 across the 4 of their papers we have counts for
4 papers
MoExtend: Tuning New Experts for Modality and Task Extension
Shanshan Zhong, Shanghua Gao, Zhongzhan Huang +3
Large language models (LLMs) excel in various tasks but are primarily trained on text data, limiting their application scope. Expanding LLM capabilities to include vision-language…
Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima
Shanshan Zhong, Zhongzhan Huang, Daifeng Li +3
Multimodal recommender systems utilize various types of information to model user preferences and item features, helping users discover items aligned with their interests. The inte…
LSAS: Lightweight Sub-attention Strategy for Alleviating Attention Bias Problem
Shanshan Zhong, Wushao Wen, Jinghui Qin +2
In computer vision, the performance of deep neural networks (DNNs) is highly related to the feature extraction ability, i.e., the ability to recognize and focus on key pixel region…
Mix-Pooling Strategy for Attention Mechanism
Shanshan Zhong, Wushao Wen, Jinghui Qin
Recently many effective attention modules are proposed to boot the model performance by exploiting the internal information of convolutional neural networks in computer vision. In…