Michelangelo: An Artificial Intelligence Framework for Evaluating Long-Context Reasoning in Large Language Models Beyond Simple Retrieval Tasks

Michelangelo AI Framework offers practical solutions for challenges in long-context reasoning by introducing Latent Structure Queries to evaluate models' ability to synthesize scattered data points across lengthy datasets. Tasks in the framework include Latent List, Multi-Round Coreference Resolution, and the IDK task to test models' abilities in handling complex scenarios. Performance insights from Michelangelo evaluations show differences among models like GPT-4, Claude 3, and Gemini, highlighting varying accuracies in handling long-context tasks. By pushing the boundaries of measuring long-context understanding in large language models, Michelangelo advances AI reasoning capabilities. For more information on Michelangelo and AI solutions, follow us on Twitter and join our Telegram Channel and LinkedIn Group.