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Artificial Intelligence › Core AI ›

Explainability

41 papers

Papers per year

2

3

1

3

32

Papers

Thesis Proposal: An Explainable Multimodal Framework for Detecting Harmful Content in Code-Switched Children’s Media ACL 2026

Faithfulness Beyond Plausibility: Auditing Human Explanations in Educational Assessment ACL 2026

Actionable Interpretability for Churn Classification: A Text Bottleneck Model Case Study at a Major Telecom Provider ACL 2026

Robust Explanations for User Trust in Enterprise NLP Systems ACL 2026

FunnyNodules: A Customizable Medical Dataset Tailored for Evaluating Explainable AI MIDL 2026

SoftCAM: Making black box models self-explainable for medical image analysis MIDL 2026

Explainable Pathomics Feature Visualization via Correlation-aware Conditional Feature Editing MIDL 2026

ScamNet: Toward Explainable Large Language Model-Based Fraudulent Shopping Website Detection AAAI 2025

Trustworthy Medical Question Answering: An Evaluation-Centric Survey EMNLP 2025

Feature Attribution for Deep Learning Models through Total Variance Decomposition MIDL 2025

Factual and Informative Review Generation for Explainable Recommendation AAAI 2023

Explaining Preferences with Shapley Values NIPS 2022

Actionable Model-Centric Explanations (Student Abstract) AAAI 2022

Explainable Assessment of Healthcare Articles with QA ACL 2022

RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions AAAI 2021

Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human Ratings EMNLP 2021