AI RESEARCH
From Residuals to Reasons: LLM-Guided Mechanism Inference from Tabular Data
arXiv CS.LG
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ArXi:2605.22897v1 Announce Type: new A persistent challenge in machine learning for scientific applications is jointly achieving prediction and understanding. Statistical models excel on structured data but operate as black boxes, while existing interpretability methods are largely inspective: they answer "which features matter?" but do not articulate how features interact or refine explanations iteratively alongside human understanding.