1 citations · 1 across the 5 of their papers we have counts for
7 papers
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…
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…
Resolving Evidence Sparsity: Agentic Context Engineering for Long-Document Understanding
Keliang Liu, Zizhi Chen, Mingcheng Li +3
Document understanding is a long standing practical task. Vision Language Models (VLMs) have gradually become a primary approach in this domain, demonstrating effective performance…
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…
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…
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…