This article explores how to use LLMLingua, a tool developed by Microsoft, to compress prompts for large language models, reducing costs and improving efficiency without retraining models.
This paper proposes the Knowledge Graph of Thoughts (KGoT) architecture for AI assistants, integrating LLM reasoning with dynamically constructed knowledge graphs to reduce costs and improve performance on complex tasks like the GAIA benchmark.
