Author

Yi-Xin Yang

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#machine learning Review Jul 2026

Retrieval-Augmented Interpretable Learning: Towards Task-Specific Zero-Shot Models in Healthcare

We introduce Retrieval-Augmented Interpretable Learning (RAIL), a probabilistic meta-learning framework for zero-shot generation of task-specific interpretable models that synthesizes coefficient-space structure from natural-language task descriptions and a memory of previously learned task-specific predictors. RAIL re...

Sazan Mahbub, Caleb N. Ellington, Zhi-Yuan Li et al. · arXiv.org · 1 citation

Preprint Jul 2026

Context-Adaptive Inference: A Unified Statistical and Foundation-Model View

This article provides a unified view of context-adaptive inference across three traditions that are usually treated separately: explicit adaptation in statistics, rapid task-specific adaptation in meta-learning and transfer, and implicit adaptation in large foundation models via prompting, retrieval, and expert routing...

Yueting Yao, Caleb N. Ellington, Jingyun Jia et al. · 0 citations