17 citations · 23 across the 6 of their papers we have counts for
6 papers
MoRA: LoRA Guided Multi-Modal Disease Diagnosis with Missing Modality
Zhiyi Shi, Junsik Kim, Wanhua Li +2
Multi-modal pre-trained models efficiently extract and fuse features from different modalities with low memory requirements for fine-tuning. Despite this efficiency, their applicat…
Joint-Task Regularization for Partially Labeled Multi-Task Learning
Kento Nishi, Junsik Kim, Wanhua Li +1
Multi-task learning has become increasingly popular in the machine learning field, but its practicality is hindered by the need for large, labeled datasets. Most multi-task learnin…
CLIPTrans: Transferring Visual Knowledge with Pre-trained Models for Multimodal Machine Translation
Devaansh Gupta, Siddhant Kharbanda, Jiawei Zhou +3
There has been a growing interest in developing multimodal machine translation (MMT) systems that enhance neural machine translation (NMT) with visual knowledge. This problem setup…
Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis
Shuai Shen, Wanhua Li, Zheng Zhu +3
Talking head synthesis is an emerging technology with wide applications in film dubbing, virtual avatars and online education. Recent NeRF-based methods generate more natural talki…
Label2Label: A Language Modeling Framework for Multi-Attribute Learning
Wanhua Li, Zhexuan Cao, Jianjiang Feng +2
Objects are usually associated with multiple attributes, and these attributes often exhibit high correlations. Modeling complex relationships between attributes poses a great chall…
MetaAge: Meta-Learning Personalized Age Estimators
Wanhua Li, Jiwen Lu, Abudukelimu Wuerkaixi +2
Different people age in different ways. Learning a personalized age estimator for each person is a promising direction for age estimation given that it better models the personaliz…