causal feature identification 1domain shift 1model-agnostic diagnostics 1post-hoc analysis 1sensitivity analysis 1
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cs.AI2026
From Training to Deployment: Post-Hoc Causal Feature Identification via Sensitivity Ratios
Athanasios Vlontzos, Giorgos Papanastasiou, Bernhard Kainz +1
The paper proposes the Normalised Sensitivity Ratio (NSR), a post‑hoc, model‑agnostic method to distinguish causal from spurious features by comparing model sensitivity across envi…
cs.AI2026
Entangled by Design: Spurious Intra-Variable Signal Routing in Tabular In-Context Learners
Athanasios Vlontzos, Giorgos Papanastasiou, Bernhard Kainz +1
Consider a model trained at a single hospital to predict patient recovery, where the measured feature bundles the patient's true health signal () with a systematic artefact…