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cs.CV2026
Position: Explanation Stability Is a Property of the Model Method Pair, Not the Model
Kabilan Elangovan, Daniel Ting
This position paper argues that claims about explanation stability are scientifically invalid without cross method validation. Just as statistical significance requires the test st…
cs.CV2026
When Fine-Tuning Changes the Evidence: Architecture-Dependent Semantic Drift in Chest X-Ray Explanations
Kabilan Elangovan, Daniel Ting
Transfer learning followed by fine-tuning is widely adopted in medical image classification due to consistent gains in diagnostic performance. However, in multi-class settings with…
cs.CV2026
Quantifying Explanation Consistency: The C-Score Metric for CAM-Based Explainability in Medical Image Classification
Kabilan Elangovan, Daniel Ting
Class Activation Mapping (CAM) methods are widely used to generate visual explanations for deep learning classifiers in medical imaging. However, existing evaluation frameworks ass…