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Explainable Ai

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Explainable Ai

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Research Frontiers in Model-Agnostic Local Approximation

Techniques like LIME that approximate complex models locally with interpretable models for instance-level explanations.

Counterfactual Explanations and Causal Reasoning in Black Boxes
Local Feature Interactions Beyond Linear Approximations
Temporal Dynamics in Locally Explainable Decision Boundaries
Adversarial Robustness of Model-Agnostic Explanations
Fidelity-Interpretability Trade-offs in Local Surrogate Models
Shapley Value Approximations for High-Dimensional Feature Spaces
Multi-Modal Local Explanations Across Heterogeneous Data Types
Instance-Level Uncertainty Quantification in Local Approximations
Prototype-Based Local Explanations for Semantic Understanding
Attention Mechanisms as Local Explanation Proxies

All Explainable AI PhD categories