For developers and EPCs building multi-state portfolios, engineering that anticipates variances in interconnection ...

The article explains that audits and investigations serve distinct legal purposes under GST and require different taxpayer responses. Understanding this distinction is crucial to safeguarding ...

Abstract: Prompt-based learning has demonstrated remarkable success in few-shot text classification, outperforming the traditional fine-tuning approach. This method transforms a text input into a ...

Organisations worldwide are racing to develop a universally recognised label for "human-made" products and services as part of the growing backlash against AI use. Declarations like "Proudly Human", ...

The bias problem in classification tasks and the different strategies used for bias mitigation. How these strategies are grouped into categories and a brief introduction of the most representative ...

For this report, Reddit posts and comments were classified using the following prompts to GPT-4.1 mini. The prompts were designed to mirror the codebooks that our research team used to create the ...

The International Classification of Diseases, or ICD, is a classification system for all physical and mental diseases produced by the World Health Organization (WHO). It’s used for diagnosis, research ...

NeuralClassifier is designed for quick implementation of neural models for hierarchical multi-label classification task, which is more challenging and common in real-world scenarios. A salient feature ...

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...

Section 1. Purpose. Across the country, ideologues who deny the biological reality of sex have increasingly used legal and other socially coercive means to permit men to self-identify as women and ...

Deep neural networks are increasingly used in medical imaging for tasks such as pathological classification, but they face challenges due to the scarcity of high-quality, expert-labeled training data.