Vision-language foundation models (VLMs) for computed tomography (CT) are emerging tools that learn generalizable representations from large-scale clinical imaging data. While these models can predict task-specific labels, the extent to which their representations capture the clinical, physiological, and longitudinal...
C. Beeche, Joonghyun Kim, H. Tavolinejad et al.· npj Digital Medicine· 1 citation
This tutorial delivers a systematic, data-centric roadmap to build LLM agents that are not merely capable but provably trustworthy, unifying advances in LLM agents, robust machine learning, and data-centric AI.
Tian-Long Chen, Jian Pei, Minxing Zhang et al.· Proceedings of the 32nd ACM...· 0 citations
Large language model (LLM) based agents are evolving from conversational chatbots into autonomous decision-makers that plan, reason, wield tools, and collaborate across high-stakes domains such as healthcare, finance, and scientific discovery. Yet this power brings a fundamental challenge: trustworthiness. How can we g...
Tianlong Chen, Jian Pei, Minxing Zhang et al.· Proceedings of the 32nd ACM...· 0 citations
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