A comprehensive analysis of AI usage patterns based on 100 trillion tokens of real-world LLM traffic from OpenRouter, revealing the shift toward reasoning models and agentic inference workflows. The study examines how …
This study analyzes the troubled implementations of Epic EHR systems in Denmark and Finland, revealing significant post-implementation challenges including poor usability, increased task completion times, and widespread …
Comprehensive research by the UK Department for Science, Innovation & Technology reveals that only 16% of UK businesses currently use AI, with natural language processing being the most common application. The study …
DRAGON-AI is a novel method that employs Large Language Models and Retrieval Augmented Generation to automatically generate ontology components including relationships, definitions, and logical axioms. The system …
This comprehensive review examines the bidirectional relationship between AI techniques and ontologies, exploring how machine learning contributes to automated ontology construction while ontologies enhance AI system …
This paper presents an LLM-agent driven framework for dynamically discovering and organizing financial topics from quarterly earnings calls into a hierarchical ontology. The system enables analysts to track emerging …
This paper introduces FINTAGGING, the first comprehensive benchmark for evaluating large language models on XBRL tagging tasks, decomposing the complex process into financial numeric identification and concept linking …
A comprehensive walkthrough of essential probability distributions including Bernoulli, Poisson, normal, binomial, and exponential distributions, demonstrated through 30 real-world problems covering e-commerce, call …
