dailyai.report

A new research paper proposes a mechanism‑aware evaluation that blends symbolic rules with mechanistic interpretability, exposing models’ reliance on shortcuts rather than true generalization. By testing identical architectures on the NL‑to‑SQL task, the study shows that conventional accuracy masks memorization, while the new pass/fail metric reveals genuine grounding.