gradient attribution

GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs ACL 2026 Image-based Outlier Synthesis With Training Data CVPR 2026 Data Shapley in One Training Run ICLR 2025 Extract Free Dense Misalignment from CLIP AAAI 2025 LibraGrad: Balancing Gradient Flow for Universally Better Vision Transformer Attributions CVPR 2025 Towards Understanding Multi-Task Learning (Generalization) of LLMs via Detecting and Exploring Task-Specific Neurons COLING 2025 GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection NeurIPS 2023 Gradient-Based Uncertainty Attribution for Explainable Bayesian Deep Learning CVPR 2023 Painsight: An Extendable Opinion Mining Framework for Detecting Pain Points Based on Online Customer Reviews ACL 2023 TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization ICLR 2023 AttCAT: Explaining Transformers via Attentive Class Activation Tokens NeurIPS 2022 NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights AAAI 2022 Robust Models Are More Interpretable Because Attributions Look Normal ICML 2022 Explaining Deep Neural Network Models with Adversarial Gradient Integration IJCAI 2021 Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability ICLR 2021 Telling BERT’s Full Story: from Local Attention to Global Aggregation EACL 2021 On Identifiability in Transformers ICLR 2020 Bias Also Matters: Bias Attribution for Deep Neural Network Explanation ICML 2019 Towards Understanding Neural Machine Translation with Word Importance EMNLP 2019