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Tianqi Xiang

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Preprint Aug 2026

CACSurv: Concordance-Aligned Comparative Learning with Large Language Models for Cancer Survival Prediction

CACSurv reformulates survival modeling as mini-cohort comparative reasoning, where an LLM predicts relative prognostic orderings and introduces concordance-aligned rewards derived from comparable relations under right censoring, enabling censored outcomes to provide ranking supervision without exact event-time targets.

Tianqi Xiang, Qixiang Zhang, Xinpeng Ding et al. · 0 citations

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