3 papers
cs.LG2026
TabChange: Precise Attribute Changes in Tabular Data
Arjun Dahal, Yu Lei, Raghu N. Kacker +1
Modifying an attribute in tabular data often introduces an unnatural instance by breaking its relationships with other attributes. The modified instance must be both natural and mi…
cs.CV2026
DD-CAM: Minimal Sufficient Explanations for Vision Models Using Delta Debugging
Krishna Khadka, Yu Lei, Raghu N. Kacker +1
We introduce a gradient-free framework for identifying minimal, sufficient, and decision-preserving explanations in vision models by isolating the smallest subset of representation…
cs.LG2025
ABLE: Using Adversarial Pairs to Construct Local Models for Explaining Model Predictions
Krishna Khadka, Sunny Shree, Pujan Budhathoki +3
Machine learning models are increasingly used in critical applications but are mostly "black boxes" due to their lack of transparency. Local explanation approaches, such as LIME, a…