Diagnostic Reasoning Benchmark

Diagnostic reasoning benchmarks are designed to rigorously evaluate the capabilities of artificial intelligence models, particularly large language models (LLMs), in performing complex reasoning tasks across diverse domains. Current research focuses on developing benchmarks that assess not only accuracy but also robustness to various challenges, including handling incomplete information, managing multiple data modalities (e.g., text, images, video), and generalizing to unseen scenarios. These benchmarks are crucial for advancing the development of reliable and trustworthy AI systems, with applications ranging from clinical diagnosis and medical image analysis to more general problem-solving tasks.