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Interpretability

105 papers

Papers per year

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Papers

Improving Explainable Fact-Checking via Sentence-Level Factual Reasoning EMNLP 2024
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency NIPS 2023
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks NIPS 2023
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations NIPS 2023
SmoothHess: ReLU Network Feature Interactions via Stein's Lemma NIPS 2023
Towards Better Visualizing the Decision Basis of Networks via Unfold and Conquer Attribution Guidance AAAI 2023
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis AAAI 2023
Improving Interpretability via Explicit Word Interaction Graph Layer AAAI 2023
Testing the Channels of Convolutional Neural Networks AAAI 2023
Log-linear Guardedness and its Implications ACL 2023
Adversarial Normalization: I Can Visualize Everything (ICE) CVPR 2023
Towards a Mechanistic Interpretation of Multi-Step Reasoning Capabilities of Language Models EMNLP 2023
VISIT: Visualizing and Interpreting the Semantic Information Flow of Transformers EMNLP 2023
Revisiting Sparse Convolutional Model for Visual Recognition NIPS 2022
DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training AAAI 2022
Visual Explanations for Convolutional Neural Networks via Latent Traversal of Generative Adversarial Networks (Student Abstract) AAAI 2022
Is Attention Explanation? An Introduction to the Debate ACL 2022
Explaining Classes through Stable Word Attributions ACL 2022
B-Cos Networks: Alignment Is All We Need for Interpretability CVPR 2022
Finding Skill Neurons in Pre-trained Transformer-based Language Models EMNLP 2022
Tracing and Manipulating intermediate values in Neural Math Problem Solvers EMNLP 2022
Improving Deep Learning Interpretability by Saliency Guided Training NIPS 2021
HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks AAAI 2021
Interpreting Multivariate Shapley Interactions in DNNs AAAI 2021
Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations AAAI 2021