3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers
Evgenii Kuriabov, David Miller, Jia Li
In this work, we propose a unified approach for diagnosing misclassification and assessing the robustness of black-box classifiers. Central to our method is an optimization framewo…
cs.CL2026★ 3 cited
Large language models show fragile cognitive reasoning about human emotions
Sree Bhattacharyya, Evgenii Kuriabov, Lucas Craig +4
Affective computing seeks to support the holistic development of artificial intelligence by enabling machines to engage with human emotion. Recent foundation models, particularly l…
stat.ME2024
SynthTree: Co-supervised Local Model Synthesis for Explainable Prediction
Evgenii Kuriabov, Jia Li
Explainable machine learning (XML) has emerged as a major challenge in artificial intelligence (AI). Although black-box models such as Deep Neural Networks and Gradient Boosting of…