The AI Fairness and Explainability Toolkit is an open-source platform designed to evaluate, visualize, and improve AI models with a focus on fairness, explainability, and ethical considerations.

When this data is organized chronologically—tracking changes in a specific metric over time—it becomes time-series data.

The micro mobile data center market is growing as industries adopt edge computing, IoT, and AI for faster local processing, boosting demand for modular, portable, and energy-efficient infrastructure ...

Abstract: Evaluating Large Language Models (LLMs) for AI alignment necessitates methodologies that go beyond general-purpose benchmarks to address domain-specific challenges and ethical complexities.

Abstract: Image translation has wide applications, such as style transfer and modality conversion, usually aiming to generate images having both high degrees of realism and faithfulness. These ...

Altmetrics have emerged as a complementary tool to traditional citation-based metrics in the assessment of scholarly impact. Unlike traditional metrics that primarily capture academic citations over ...