CodeSwift introduces a novel framework that significantly improves the efficiency of LLM-based code generation by leveraging code's unique characteristics.

• Creates a multi-source datastore specifically designed for code snippets
• Implements syntax-aware retrieval methods that understand code structure
• Achieves faster inference times while maintaining code quality
• Addresses the critical need for responsiveness in coding assistance tools

This research matters because it makes AI coding assistants more practical for real-time development environments, potentially increasing developer productivity without sacrificing output quality.

CodeSwift: Accelerating LLM Inference for Efficient Code Generation