post-hoc explanation

DeltaSHAP: a Shapley Value Framework for Interpreting Political Ambiguity SemEval 2026 Distribution-Based Feature Attribution for Explaining the Predictions of Any Classifier AAAI 2026 EPIC: Explanation of Pretrained Image Classification Networks via Prototypes AAAI 2026 Faithful Serum: Mitigating the Faithfulness Gap in Textual Explanations of LLM Decisions via Attribution Guidance ACL 2026 From Nodes to Narratives: Explaining Graph Neural Networks with LLMs and Graph Context ACL 2026 Revitalizing Black-Box Interpretability: Actionable Interpretability for LLMs via Proxy Models ACL 2026 SoftCAM: Making black box models self-explainable for medical image analysis MIDL 2026 Benchmarking Time-localized Explanations for Audio Classification Models Interspeech 2025 Bringing Interpretability to Neural Audio Codecs Interspeech 2025 Efficient and Accurate Explanation Estimation with Distribution Compression ICLR 2025 Explaining Negative Classifications of AI Models in Tumor Diagnosis UAI 2025 Explanations for Multi-Agent Reinforcement Learning AAAI 2025 How to Probe: Simple Yet Effective Techniques for Improving Post-hoc Explanations ICLR 2025 Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods ICLR 2025 Axiomatic Aggregations of Abductive Explanations AAAI 2024 Boundary-Aware Uncertainty for Feature Attribution Explainers AISTATS 2024 Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers AISTATS 2024 Factorized Explainer for Graph Neural Networks AAAI 2024 Faithful and Plausible Natural Language Explanations for Image Classification: A Pipeline Approach EMNLP 2024 Improving Explainable Fact-Checking via Sentence-Level Factual Reasoning EMNLP 2024 Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image Classification IJCAI 2024 Listenable Maps for Zero-Shot Audio Classifiers NeurIPS 2024 On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods AAAI 2024 Provably Better Explanations with Optimized Aggregation of Feature Attributions ICML 2024 Self-AMPLIFY: Improving Small Language Models with Self Post Hoc Explanations EMNLP 2024