SymRAG adaptively routes queries through neuro-symbolic, neural, or hybrid paths based on complexity and system load, ensuring efficient and accurate RAG for diverse QA tasks.

The source codes for bachelor's thesis

Resource-efficient LLM distillation: Improving sustainability and reducing computational costs of Large Language Models in financial analytics through knowledge distillation.