integrated gradient

Calibration vs Decision Making: Revisiting the Reliability Paradox in Unlearned Language Models ACL 2026 Contrastive Integrated Gradients: A Feature Attribution-Based Method for Explaining Whole Slide Image Classification WACV 2026 Fine-Grained Post-Training Quantization for Large Vision Language Models with Quantization-Aware Integrated Gradients CVPR 2026 Global Information Thresholding for Sufficient and Necessary Circuits CVPR 2026 GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs ACL 2026 H-Sets: Hessian-Guided Discovery of Set-Level Feature Interactions in Image Classifiers CVPR 2026 Mitigating Copy Bias in In-Context Learning through Neuron Pruning EACL 2026 Transform to Transfer: Boosting Adversarial Attack Transferability on Vision-Language Pre-training Models CVPR 2026 ADD: Attribution-Driven Data Augmentation Framework for Boosting Image Super-Resolution CVPR 2025 Audio-Based Classification and Geographic Regression of Austrian Dialects Interspeech 2025 Differentially Private Integrated Decision Gradients (IDG-DP) for Radar-Based Human Activity Recognition WACV 2025 Evaluating Input Feature Explanations through a Unified Diagnostic Evaluation Framework NAACL 2025 FitCF: A Framework for Automatic Feature Importance-guided Counterfactual Example Generation ACL 2025 Four Axiomatic Characterizations of the Integrated Gradients Attribution Method JMLR 2025 Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability AISTATS 2025 GEFA: A General Feature Attribution Framework Using Proxy Gradient Estimation ICML 2025 Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path AAAI 2025 InteDisUX: Intepretation-Guided Discriminative User-Centric Explanation for Time Series AAAI 2025 TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation ICML 2025 CIDR: A Cooperative Integrated Dynamic Refining Method for Minimal Feature Removal Problem AAAI 2024 Comparative Study of Explainability Methods for Legal Outcome Prediction EMNLP 2024 Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models ACL 2024 Denoising Diffusion Path: Attribution Noise Reduction with An Auxiliary Diffusion Model NeurIPS 2024 Dynamic Multi-granularity Attribution Network for Aspect-based Sentiment Analysis EMNLP 2024 Explaining Pre-Trained Language Models with Attribution Scores: An Analysis in Low-Resource Settings COLING 2024