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Interpretability

7,452 papers

Papers per year

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Papers

Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models AISTATS 2023
Feasible Recourse Plan via Diverse Interpolation AISTATS 2023
A Sea of Words: An In-Depth Analysis of Anchors for Text Data AISTATS 2023
Manifold Restricted Interventional Shapley Values AISTATS 2023
Heavy Sets with Applications to Interpretable Machine Learning Diagnostics AISTATS 2023
Distill n’ Explain: explaining graph neural networks using simple surrogates AISTATS 2023
Unifying local and global model explanations by functional decomposition of low dimensional structures AISTATS 2023
On double-descent in uncertainty quantification in overparametrized models AISTATS 2023
Probabilistic Conformal Prediction Using Conditional Random Samples AISTATS 2023
Adversarial robustness of VAEs through the lens of local geometry AISTATS 2023
On the Privacy Risks of Algorithmic Recourse AISTATS 2023
Semantic Strengthening of Neuro-Symbolic Learning AISTATS 2023
Efficient SAGE Estimation via Causal Structure Learning AISTATS 2023
Backtracking Counterfactuals CLEAR 2023
ToMChallenges: A Principle-Guided Dataset and Diverse Evaluation Tasks for Exploring Theory of Mind CONLL 2023
A Comparative Study on Textual Saliency of Styles from Eye Tracking, Annotations, and Language Models CONLL 2023
The Validity of Evaluation Results: Assessing Concurrence Across Compositionality Benchmarks CONLL 2023
Revising with a Backward Glance: Regressions and Skips during Reading as Cognitive Signals for Revision Policies in Incremental Processing CONLL 2023
Theory of Mind in Large Language Models: Examining Performance of 11 State-of-the-Art models vs. Children Aged 7-10 on Advanced Tests CONLL 2023
Future Lens: Anticipating Subsequent Tokens from a Single Hidden State CONLL 2023
Implications of Annotation Artifacts in Edge Probing Test Datasets CONLL 2023
REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization CONLL 2023
X-Pruner: eXplainable Pruning for Vision Transformers CVPR 2023
PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification CVPR 2023
Analyzing and Diagnosing Pose Estimation With Attributions CVPR 2023