Papers Explainable artificial intelligence
“Explainable artificial intelligence” 태그가 달린 논문 971편 · 필터 해제
Explanation User Interfaces: A Systematic Literature Review
Artificial Intelligence (AI) is one of the major technological advancements of this century, bearing incredible potential for users through AI-powered applications and tools in numerous domains. Being often black-box (i.…
Decision MakingExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Systematic Literature ReviewFrom What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI
Counterfactuals play a pivotal role in the two distinct data science fields of causal inference (CI) and explainable artificial intelligence (XAI). While the core idea behind counterfactuals remains the same in both fiel…
Causal InferencecounterfactualExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Addressing the Scarcity of Benchmarks for Graph XAI
While Graph Neural Networks (GNNs) have become the de facto model for learning from structured data, their decisional process remains opaque to the end user, undermining their deployment in safety-critical applications. …
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Graph ClassificationMost General Explanations of Tree Ensembles (Extended Version)
Explainable Artificial Intelligence (XAI) is critical for attaining trust in the operation of AI systems. A key question of an AI system is ``why was this decision made this way''. Formal approaches to XAI use a formal m…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Heart2Mind: Human-Centered Contestable Psychiatric Disorder Diagnosis System using Wearable ECG Monitors
Psychiatric disorders affect millions globally, yet their diagnosis faces significant challenges in clinical practice due to subjective assessments and accessibility concerns, leading to potential delays in treatment. To…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Heart Rate VariabilityTime SeriesWebXAII: an open-source web framework to study human-XAI interaction
This article introduces WebXAII, an open-source web framework designed to facilitate research on human interaction with eXplainable Artificial Intelligence (XAI) systems. The field of XAI is rapidly expanding, driven by …
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)PnPXAI: A Universal XAI Framework Providing Automatic Explanations Across Diverse Modalities and Models
Recently, post hoc explanation methods have emerged to enhance model transparency by attributing model outputs to input features. However, these methods face challenges due to their specificity to certain neural network …
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)SpecificityFinancial Fraud Detection Using Explainable AI and Stacking Ensemble Methods
Traditional machine learning models often prioritize predictive accuracy, often at the expense of model transparency and interpretability. The lack of transparency makes it difficult for organizations to comply with regu…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Feature Importancefeature selection+1SIM-Shapley: A Stable and Computationally Efficient Approach to Shapley Value Approximation
Explainable artificial intelligence (XAI) is essential for trustworthy machine learning (ML), particularly in high-stakes domains such as healthcare and finance. Shapley value (SV) methods provide a principled framework …
Computational EfficiencyExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Stochastic OptimizationTuning for Trustworthiness -- Balancing Performance and Explanation Consistency in Neural Network Optimization
Despite the growing interest in Explainable Artificial Intelligence (XAI), explainability is rarely considered during hyperparameter tuning or neural architecture optimization, where the focus remains primarily on minimi…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Model SelectionDiscovering Concept Directions from Diffusion-based Counterfactuals via Latent Clustering
Concept-based explanations have emerged as an effective approach within Explainable Artificial Intelligence, enabling interpretable insights by aligning model decisions with human-understandable concepts. However, existi…
ClusteringcounterfactualExplainable artificial intelligenceExplainable Artificial Intelligence Techniques for Software Development Lifecycle: A Phase-specific Survey
Artificial Intelligence (AI) is rapidly expanding and integrating more into daily life to automate tasks, guide decision making, and enhance efficiency. However, complex AI models, which make decisions without providing …
counterfactualExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)SurveyPrivacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Explainable Artificial Intelligence (XAI) has emerged as a pillar of Trustworthy AI and aims to bring transparency in complex models that are opaque by nature. Despite the benefits of incorporating explanations in models…
ArticlesExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Privacy PreservingMultimodal Doctor-in-the-Loop: A Clinically-Guided Explainable Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer
This study proposes a novel approach combining Multimodal Deep Learning with intrinsic eXplainable Artificial Intelligence techniques to predict pathological response in non-small cell lung cancer patients undergoing neo…
Data IntegrationDeep LearningExplainable artificial intelligenceMultimodal Deep LearningExplainable AI in Spatial Analysis
This chapter discusses the opportunities of eXplainable Artificial Intelligence (XAI) within the realm of spatial analysis. A key objective in spatial analysis is to model spatial relationships and infer spatial processe…
Bias DetectionExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Machine Learning Meets Transparency in Osteoporosis Risk Assessment: A Comparative Study of ML and Explainability Analysis
The present research tackles the difficulty of predicting osteoporosis risk via machine learning (ML) approaches, emphasizing the use of explainable artificial intelligence (XAI) to improve model transparency. Osteoporos…
Clinical KnowledgeExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Feature ImportanceXBreaking: Explainable Artificial Intelligence for Jailbreaking LLMs
Large Language Models are fundamental actors in the modern IT landscape dominated by AI solutions. However, security threats associated with them might prevent their reliable adoption in critical application scenarios su…
Explainable artificial intelligenceDiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning
Explainable artificial intelligence (XAI) has become increasingly important in decision-critical domains such as healthcare, finance, and law. Counterfactual (CF) explanations, a key approach in XAI, provide users with a…
counterfactualDiversityExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)ApproXAI: Energy-Efficient Hardware Acceleration of Explainable AI using Approximate Computing
Explainable artificial intelligence (XAI) enhances AI system transparency by framing interpretability as an optimization problem. However, this approach often necessitates numerous iterations of computationally intensive…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Generative and Explainable AI for High-Dimensional Channel Estimation
In this paper, we propose a new adversarial training framework to address high-dimensional instantaneous channel estimation in wireless communications. Specifically, we train a generative adversarial network to predict a…
Explainable artificial intelligenceGenerative Adversarial Network