8 papers
A Utility-preserving De-identification Pipeline for Cross-hospital Radiology Data Sharing
Chenhao Liu, Zelin Wen, Yan Tong +7
Large-scale radiology data are critical for developing robust medical AI systems. However, sharing such data across hospitals remains heavily constrained by privacy concerns. Exist…
Bipartite Mode Matching for Vision Training Set Search from a Hierarchical Data Server
Yue Yao, Ruining Yang, Tom Gedeon
We explore a situation in which the target domain is accessible, but real-time data annotation is not feasible. Instead, we would like to construct an alternative training set from…
SAIL-Embedding Technical Report: Omni-modal Embedding Foundation Model
Lin Lin, Jiefeng Long, Zhihe Wan +15
Multimodal embedding models aim to yield informative unified representations that empower diverse cross-modal tasks. Despite promising developments in the evolution from CLIP-based…
Accelerating Time Series Foundation Models with Speculative Decoding
Pranav Subbaraman, Fang Sun, Jinxi Yu +4
Time series forecasting drives operational decisions under tight latency budgets, and autoregressive time series foundation models (TSFMs) increasingly deliver the most accurate fo…
Integrating Feature Attention and Temporal Modeling for Collaborative Financial Risk Assessment
Yue Yao, Zhen Xu, Youzhu Liu +3
This paper addresses the challenges of data privacy and collaborative modeling in cross-institution financial risk analysis. It proposes a risk assessment framework based on federa…
Unsupervised Search for Ethnic Minorities' Medical Segmentation Training Set
Yixiao Chen, Yue Yao, Ruining Yang +3
This article investigates the critical issue of dataset bias in medical imaging, with a particular emphasis on racial disparities caused by uneven population distribution in datase…
Labels Generated by Large Language Models Help Measure People's Empathy in Vitro
Md Rakibul Hasan, Yue Yao, Md Zakir Hossain +4
Large language models (LLMs) have revolutionised many fields, with LLM-as-a-service (LLMSaaS) offering accessible, general-purpose solutions without costly task-specific training.…
Ranked from Within: Ranking Large Multimodal Models Without Labels
Weijie Tu, Weijian Deng, Dylan Campbell +4
Can the relative performance of a pre-trained large multimodal model (LMM) be predicted without access to labels? As LMMs proliferate, it becomes increasingly important to develop…