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Junxian Wu

5 accepted papers

2026

IVQ: Structured and Lightweight Vector Quantization via Binary Hierarchical Composition Inspired by $\textit{IChing}$

ICML 2026poster

Vector Quantization (VQ) has been widely used in visual and audio representation due to its effectiveness in compressing high-dimensional signals. However, existing VQ methods often rely on large and unstructured codebooks, which leads to inefficient code utilization and frequent codebook collapse. …

Cited by 0SourceScholar
2026

MOON2.0: Dynamic Modality-balanced Multimodal Representation Learning for E-commerce Product Understanding

CVPR 2026

Recent Multimodal Large Language Models (MLLMs) have significantly advanced e-commerce product understanding. However, they still face three challenges: (i) the modality imbalance induced by modality mixed training; (ii) underutilization of the intrinsic alignment relationships among visual and text

Cited by 0SourceScholar
2025

GVMGen: A General Video-to-Music Generation Model with Hierarchical Attentions

AAAI 2025technical

Composing music for video is essential yet challenging, leading to a growing interest in automating music generation for video applications. Existing approaches often struggle to achieve robust music-video correspondence and generative diversity, primarily due to inadequate feature alignment methods…

Cited by 3SourcePDFScholar
2025

Learning Heterogeneous Tissues with Mixture of Experts for Gigapixel Whole Slide Images

CVPR 2025poster

Analyzing gigapixel Whole Slide Images (WSIs) is challenging due to the complex pathological tissue environment and the absence of target-driven domain knowledge. Previous methods incorporated pathological priors to mitigate this issue but relied on additional inference steps and specialized workflo…

2024

Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images

NeurIPS 2024poster

Survival prediction is a significant challenge in cancer management. Tumor micro-environment is a highly sophisticated ecosystem consisting of cancer cells, immune cells, endothelial cells, fibroblasts, nerves and extracellular matrix. The intratumor heterogeneity and the interaction across multiple…

Cited by 3SourcePDFScholar