Amlan Chakrabarti

Abstract Quadratic attention enhances interaction capacity in Transformer models but leads to rapid growth in computational demands as attention rank increases. This paper presents a bounded-rank quadratic attention mechanism where fixed-dimensional feature encodings determine the interaction space and enforce a strict upper bound on attention rank.

Abstract Explainable Artificial Intelligence (XAI) performs a vital role in ensuring transparency, trust, and accountability in clinical decision support systems. However, most existing XAI techniques such as SHAP, LIME, Grad-CAM, and DeepLIFT provide post-hoc explanations without quantifying trust, ethical alignment, and governance readiness. As a result, interpretability alone does not reliably translate into dependable AI-based clinical decision support systems.

CONFLICT OF INTEREST STATEMENT The authors declare no conflicts of interest. REFERENCES 1, . Multiprocessor synchronization and hierarchical scheduling. Proc. IEEE Intl. Conf. On parallel processing workshops, Vienna, Austria, 2009, pp. 58–64. 2009. 2, , , . Partitioned fixed-priority real-time scheduling based on dependent task-Split on multicore Platform. Proc.12th IEEE Intl. Conf. On trust, security and privacy in comp. And Comm., Melbourne, VIC, Australia, 2013, pp. 1257–1264. 2013. 3, .