AI RESEARCH
Empirical Characterization of Rationale Stability Under Controlled Perturbations for Explainable Pattern Recognition
arXiv CS.AI
•
ArXi:2604.04456v1 Announce Type: new Reliable pattern recognition systems should exhibit consistent behavior across similar inputs, and their explanations should remain stable. However, most Explainable AI evaluations remain instance centric and do not explicitly quantify whether attribution patterns are consistent across samples that share the same class or represent small variations of the same input.