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Interpretability
173 directly classified papers
Papers per year
2013: 1
2015: 1
2016: 2
2017: 1
2018: 6
2019: 9
2020: 24
2021: 31
2022: 34
2023: 15
2024: 20
2025: 29
Papers
Walking the Web of Concept-Class Relationships in Incrementally Trained Interpretable Models
AAAI 2025
Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis
CVPR 2025
Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests
AAAI 2025
Attributive Reasoning for Hallucination Diagnosis of Large Language Models
AAAI 2025
Selective Explanations
NIPS 2024
Learnable Privacy Neurons Localization in Language Models
ACL 2024
Stochastic Concept Bottleneck Models
NIPS 2024
Are self-explanations from Large Language Models faithful?
ACL 2024
Do Large Language Models Know How Much They Know?
EMNLP 2024
The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis
EMNLP 2024
Too Big to Fail: Larger Language Models are Disproportionately Resilient to Induction of Dementia-Related Linguistic Anomalies
ACL 2024
Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics
EMNLP 2024
Data-faithful Feature Attribution: Mitigating Unobservable Confounders via Instrumental Variables
NIPS 2024
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
NIPS 2024
SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology
CVPR 2024
A General Theoretical Framework for Learning Smallest Interpretable Models
AAAI 2024
LLMs for Generating and Evaluating Counterfactuals: A Comprehensive Study
EMNLP 2024
Interpretable Mesomorphic Networks for Tabular Data
NIPS 2024
Interactive Mars Image Content-Based Search with Interpretable Machine Learning
AAAI 2024
BiasWipe: Mitigating Unintended Bias in Text Classifiers through Model Interpretability
EMNLP 2024
CAVA: A Tool for Cultural Alignment Visualization & Analysis
EMNLP 2024
LLM-Check: Investigating Detection of Hallucinations in Large Language Models
NIPS 2024
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods
AAAI 2024
Fair Multivariate Adaptive Regression Splines for Ensuring Equity and Transparency
AAAI 2024
Investigating the Saliency of Sentiment Expressions in Aspect-Based Sentiment Analysis
ACL 2023
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