arXiv AI June 9, 2026 By Varun Khurana, Vijval Ekbote, Vashu Chauhan, Yaman Kumar Singla, Rajiv Ratn Shah, Balaji Krishnamurthy

Bridging Expert Knowledge and Automated Feature Engineering via Self-Evolution

Read the original on arXiv AI →

arXiv:2606. 08800v1 Announce Type: new Abstract: In high-stakes settings such as brand compliance, clinical care, and content moderation, machine learning cannot be deployed as opaque oracles: practitioners inspect the features driving model decisions, and models must leverage the expert documentation governing these domains.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

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MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Clinical Tabular Prediction

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