LLMs for Coding

The team investigates how large language models can be tailored for code generation in constrained environments such as IoT and embedded systems. Topics include test generation, HDL synthesis, human-in-the-loop feedback, and multimodal user interaction. Their goal is to optimize for multiple objectives including power, latency, and correctness, while exploring constrained decoding and specialized small-scale LLMs.