9 papers
Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology
Tianyu Liu, Ziqing Wang, Zhaokang Liang +12
Predicting immune biomarkers associated with the tumor immune microenvironment (TIME) is critical for advancing precision oncology, yet existing approaches are largely limited to s…
HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data
Hiren Madhu, João Felipe Rocha, Tinglin Huang +3
Single-cell transcriptomics and proteomics have become a great source for data-driven insights into biology, enabling the use of advanced deep learning methods to understand cellul…
Efficient Long-Horizon Vision-Language-Action Models via Static-Dynamic Disentanglement
Weikang Qiu, Huashuo Lei, Tinglin Huang +1
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for generalist robotic control. Built upon vision-language model (VLM) architectures, VLAs predict…
TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots
Tianyu Liu, Weihao Xuan, Hao Wu +15
Advances in AI have introduced several strong models in computational pathology to usher it into the era of multi-modal diagnosis, analysis, and interpretation. However, the curren…
Steerable Instruction Following Coding Data Synthesis with Actor-Parametric Schema Co-Evolution
Tinglin Huang, Bo Chen, Xiao Zhang +2
Interpreting and following human instructions is a critical capability of large language models (LLMs) in automatic programming. However, synthesizing large-scale instruction-paire…
RephQA: Evaluating Readability of Large Language Models in Public Health Question Answering
Weikang Qiu, Tinglin Huang, Ryan Rullo +4
Large Language Models (LLMs) hold promise in addressing complex medical problems. However, while most prior studies focus on improving accuracy and reasoning abilities, a significa…