most citedTowards Unified Molecule-Enhanced Pathology Image Representation Learning via Integrating Spatial Transcriptomics

1 citations · 1 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2025

Forging a Dynamic Memory: Retrieval-Guided Continual Learning for Generalist Medical Foundation Models

Zizhi Chen, Yizhen Gao, Minghao Han +4

Multimodal biomedical Vision-Language Models (VLMs) exhibit immense potential in the field of Continual Learning (CL). However, they confront a core dilemma: how to preserve fine-g…

cs.CV2025

FysicsWorld: A Unified Full-Modality Benchmark for Any-to-Any Understanding, Generation, and Reasoning

Yue Jiang, Dingkang Yang, Minghao Han +6

Despite rapid progress in multimodal large language models (MLLMs) and emerging omni-modal architectures, current benchmarks remain limited in scope and integration, suffering from…

cs.CV2025

SatireDecoder: Visual Cascaded Decoupling for Enhancing Satirical Image Comprehension

Yue Jiang, Haiwei Xue, Minghao Han +5

Satire, a form of artistic expression combining humor with implicit critique, holds significant social value by illuminating societal issues. Despite its cultural and societal sign…

cs.CV2025

PersonaAnimator: Personalized Motion Transfer from Unconstrained Videos

Ziyun Qian, Runyu Xiao, Shuyuan Tu +7

Recent advances in motion generation show remarkable progress. However, several limitations remain: (1) Existing pose-guided character motion transfer methods merely replicate moti…

eess.IV2025

VLM-based Prompts as the Optimal Assistant for Unpaired Histopathology Virtual Staining

Zizhi Chen, Xinyu Zhang, Minghao Han +6

In histopathology, tissue sections are typically stained using common H&E staining or special stains (MAS, PAS, PASM, etc.) to clearly visualize specific tissue structures. The rap…

cs.CV2025

VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic Reconstruction

Zizhi Chen, Minghao Han, Xukun Zhang +4

Multimodal learning combining pathology images and genomic sequences enhances cancer survival analysis but faces clinical implementation barriers due to limited access to genomic s…