5 papers
Text-Guided Visual Dependency Graph Learning with Cross-Modal Attention Priors
Fei Wang, Yutong Zhang, Yang Ye +3
Estimating interpretable conditional-dependence structures from multimodal visual-linguistic features remains largely unexplored. We propose CM-GLasso (Cross-Modal Graphical Lasso)…
MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning
Yutong Zhang, Zimeng Wu, Shangcai Liao +2
Parameter-efficient transfer learning (PETL) has emerged as a pivotal paradigm for adapting pre-trained foundation models to downstream tasks, significantly reducing trainable para…
Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation
Yutong Zhang, Jiaxin Chen, Honglin Chen +5
Memory-efficient transfer learning (METL) approaches have recently achieved promising performance in adapting pre-trained models to downstream tasks. They avoid applying gradient b…
Multimodal Structure Learning: Disentangling Shared and Specific Topology via Cross-Modal Graphical Lasso
Fei Wang, Yutong Zhang, Xiong Wang
Learning interpretable multimodal representations inherently relies on uncovering the conditional dependencies between heterogeneous features. However, sparse graph estimation tech…
UniMuMo: Unified Text, Music and Motion Generation
Han Yang, Kun Su, Yutong Zhang +4
We introduce UniMuMo, a unified multimodal model capable of taking arbitrary text, music, and motion data as input conditions to generate outputs across all three modalities. To ad…