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Inter example relational distillation transfers a teacher's representation geometry by matching relations among examples within a mini batch. Computing all pairs has quadratic complexity in the batch size, whereas uniform subsampling may use a limited relation budget inefficiently. We introduce Reliability Aware Pair I...
Overall, RL-based CDSS are still partially autonomous, they often prioritize autonomy and personalization over runtime oversight, interpretability, and evaluation, and an “agentic readiness”framework is suggested to address these gaps.
A three-paradigm taxonomy (feature-based, auxiliary-based, and policy-based) based on the functional role of LLMs within the RL pipeline is proposed, which provides superior scalability and stability, though often at the expense of representational depth.
A novel Ante-hoc Explainable AI framework designed to bridge the interpretability-accuracy trade-off in high-stakes financial prognosis, specifically within credit scoring systems, which provides a verifiable and robust solution for modern, regulatory-compliant financial environments.
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