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Enhancing Counterfactual Explanation Search with Diffusion Distance and Directional Coherence
April 22, 2024, 4:41 a.m. | Marharyta Domnich, Raul Vicente
cs.LG updates on arXiv.org arxiv.org
Abstract: A pressing issue in the adoption of AI models is the increasing demand for more human-centric explanations of their predictions. To advance towards more human-centric explanations, understanding how humans produce and select explanations has been beneficial. In this work, inspired by insights of human cognition we propose and test the incorporation of two novel biases to enhance the search for effective counterfactual explanations. Central to our methodology is the application of diffusion distance, which emphasizes …
abstract adoption advance ai models arxiv cognition counterfactual cs.ai cs.lg demand diffusion human human-centric humans insights issue predictions search type understanding work
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