Code Interpreter

Code interpreters, which allow large language models (LLMs) to execute code and receive feedback, are transforming how LLMs solve complex problems, particularly in data science and software engineering. Current research focuses on developing robust benchmarks to evaluate LLMs' code interpretation capabilities, improving model architectures to enhance reasoning and safety, and exploring techniques like internal dialogues and dynamic planning to refine code generation and execution. This rapidly evolving field holds significant promise for automating complex tasks, improving code quality, and advancing the capabilities of LLMs in various scientific and practical domains.