4 citations · 10 across the 12 of their papers we have counts for
12 papers
Kalman Delta Networks: Uncertainty-aware Associative Memory
Ngoc Bui, Tinglin Huang, Rex Ying
Linear attention enables efficient long-context inference by compressing token history into a fixed-size recurrent memory. This compression makes each update a trade-off between in…
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…
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…
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…
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…
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…
Scalable Generation of Spatial Transcriptomics from Histology Images via Whole-Slide Flow Matching
Tinglin Huang, Tianyu Liu, Mehrtash Babadi +2
Spatial transcriptomics (ST) has emerged as a powerful technology for bridging histology imaging with gene expression profiling. However, its application has been limited by low th…
Beyond Feature Importance: Feature Interactions in Predicting Post-Stroke Rigidity with Graph Explainable AI
Jiawei Xu, Yonggeon Lee, Anthony Elkommos Youssef +6
This study addresses the challenge of predicting post-stroke rigidity by emphasizing feature interactions through graph-based explainable AI. Post-stroke rigidity, characterized by…
Experience Retrieval-Augmentation with Electronic Health Records Enables Accurate Discharge QA
Justice Ou, Tinglin Huang, Yilun Zhao +3
To improve the reliability of Large Language Models (LLMs) in clinical applications, retrieval-augmented generation (RAG) is extensively applied to provide factual medical knowledg…
SurfPro: Functional Protein Design Based on Continuous Surface
Zhenqiao Song, Tinglin Huang, Lei Li +1
How can we design proteins with desired functions? We are motivated by a chemical intuition that both geometric structure and biochemical properties are critical to a protein's fun…
Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer
Tinglin Huang, Zhenqiao Song, Rex Ying +1
Nucleic acid-based drugs like aptamers have recently demonstrated great therapeutic potential. However, experimental platforms for aptamer screening are costly, and the scarcity of…