DemoCraft is a novel system that improves code generation in Large Language Models by combining in-context learning, demonstration selection, and latent concept learning.

• Creates more accurate and contextually appropriate code from natural language instructions
• Uses trainable embeddings (concept tokens) to capture task-specific knowledge
• Addresses key challenges in AI code generation: semantic ambiguity and context understanding
• Offers practical applications for software development workflows and programming education

This innovation represents a significant advancement for engineering teams seeking to automate coding tasks while maintaining quality and contextual accuracy.

Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models