6 papers
GaLa: Hypergraph-Guided Visual Language Models for Procedural Planning
Kun Wang, Yiming Li, Mingcheng Qu +3
Implicit spatial relations and deep semantic structures encoded in object attributes are crucial for procedural planning in embodied AI systems. However, existing approaches often…
HMVLA: Hyperbolic Multimodal Fusion for Vision-Language-Action Models
Kun Wang, Xiao Feng, Mingcheng Qu +1
Vision Language Action (VLA) models have recently shown great potential in bridging multimodal perception with robotic control. However, existing methods often rely on direct fine-…
Spatially Gene Expression Prediction using Dual-Scale Contrastive Learning
Mingcheng Qu, Yuncong Wu, Donglin Di +4
Spatial transcriptomics (ST) provides crucial insights into tissue micro-environments, but is limited to its high cost and complexity. As an alternative, predicting gene expression…
Memory-Augmented Incomplete Multimodal Survival Prediction via Cross-Slide and Gene-Attentive Hypergraph Learning
Mingcheng Qu, Guang Yang, Donglin Di +4
Multimodal pathology-genomic analysis is critical for cancer survival prediction. However, existing approaches predominantly integrate formalin-fixed paraffin-embedded (FFPE) slide…
Multimodal Cancer Survival Analysis via Hypergraph Learning with Cross-Modality Rebalance
Mingcheng Qu, Guang Yang, Donglin Di +4
Multimodal pathology-genomic analysis has become increasingly prominent in cancer survival prediction. However, existing studies mainly utilize multi-instance learning to aggregate…
Boundary-Guided Learning for Gene Expression Prediction in Spatial Transcriptomics
Mingcheng Qu, Yuncong Wu, Donglin Di +4
Spatial transcriptomics (ST) has emerged as an advanced technology that provides spatial context to gene expression. Recently, deep learning-based methods have shown the capability…