Yucheng Wang

Distilling Holistic Knowledge with Graph Neural Networks

2021 · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Knowledge Distillation (KD) aims at transferring knowledge from a larger well-optimized teacher network to a smaller learnable student network. Existing KD methods have mainly considered two types of knowledge, namely the individual knowledge and the …

SEnsor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation

2023 · Proceedings of the AAAI Conference on Artificial Intelligence

Unsupervised Domain Adaptation (UDA) methods can reduce label dependency by mitigating the feature discrepancy between labeled samples in a source domain and unlabeled samples in a similar yet shifted target domain. Though achieving good performance, …

DREAM: Disentangling Risks to Enhance Safety Alignment in Multimodal Large Language Models

2025

Jianyu Liu, Hangyu Guo, Ranjie Duan, Xingyuan Bu, Yancheng He, Shilong Li, Hui Huang, Jiaheng Liu, Yucheng Wang, Chenchen Jing, Xingwei Qu, Xiao Zhang, Pei Wang, Yanan Wu, Jihao Gu, Yangguang Li, Jianke Zhu. Proceedings …

MDE: Modality Discrimination Enhancement for Multi-modal Recommendation

2025

Multi-modal recommendation systems aim to enhance performance by integrating an item’s content features across various modalities with user behavior data. Effective utilization of features from different modalities requires addressing two challenges: preserving semantic commonality across …

TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking

2020

Extracting entities and relations from unstructured text has attracted increasing attention in recent years but remains challenging, due to the intrinsic difficulty in identifying overlapping relations with shared entities. Prior works show that joint learning …