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cs.AI2026
Rule of Thumb: Explaining Artificial Intelligence Systems using Partial Information
Kaivalya Rawal, Daria Onitiu, Brent Mittelstadt +2
Explainable Artificial Intelligence (XAI) seeks to explain how an Artificial Intelligence (AI) system arrived at a particular decision. We propose ''Rule of Thumb'' (RoT) explanati…
cs.AI2026
Evaluating the Ability of Explanations to Disambiguate Models in a Rashomon Set
Kaivalya Rawal, Eoin Delaney, Zihao Fu +2
Explainable artificial intelligence (XAI) is concerned with producing explanations indicating the inner workings of models. For a Rashomon set of similarly performing models, expla…
cs.AI2025
Evaluating Model Explanations without Ground Truth
Kaivalya Rawal, Zihao Fu, Eoin Delaney +1
There can be many competing and contradictory explanations for a single model prediction, making it difficult to select which one to use. Current explanation evaluation frameworks…