Deep-Bench introduces a comprehensive benchmark dataset specifically designed to evaluate how well Large Language Models can generate deep learning code in real-world scenarios.

• Addresses the complexity challenges of developing deep learning systems
• Improves upon existing benchmarks by focusing on complete DL workflows rather than small snippets
• Provides a standardized evaluation framework for comparing different LLMs on coding tasks
• Enables educational applications by identifying which models best assist students and professionals learning AI development

This research has significant implications for the education sector, potentially transforming how deep learning is taught by providing AI-powered coding assistants that can generate accurate, contextually relevant code examples for learning purposes.

Deep-Bench: Deep Learning Benchmark Dataset for Code Generation