gradient-based attribution

Aggregated Attributions for Explanatory Analysis of 3D Segmentation Models WACV 2025 Extract Free Dense Misalignment from CLIP AAAI 2025 GRASP: Replace Redundant Layers with Adaptive Singular Parameters for Efficient Model Compression EMNLP 2025 Intervening in Black Box: Concept Bottleneck Model for Enhancing Human Neural Network Mutual Understanding ICCV 2025 On the Feasibility of In-Context Probing for Data Attribution NAACL 2025 Time-series attribution maps with regularized contrastive learning AISTATS 2025 Unlearning-based Neural Interpretations ICLR 2025 From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning NAACL 2024 Root Cause Explanation of Outliers under Noisy Mechanisms AAAI 2024 DecompX: Explaining Transformers Decisions by Propagating Token Decomposition ACL 2023 Gradient-Based Uncertainty Attribution for Explainable Bayesian Deep Learning CVPR 2023 Investigating the Saliency of Sentiment Expressions in Aspect-Based Sentiment Analysis ACL 2023 AttCAT: Explaining Transformers via Attentive Class Activation Tokens NeurIPS 2022 Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network NeurIPS 2022 NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights AAAI 2022 Smoothed Geometry for Robust Attribution NeurIPS 2020 Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness? ACL 2020 Towards Transparent and Explainable Attention Models ACL 2020 Towards Understanding Neural Machine Translation with Word Importance EMNLP 2019 Towards better understanding of gradient-based attribution methods for Deep Neural Networks ICLR 2018