LLM dCache

LLM-dCache focuses on optimizing the efficiency of large language models (LLMs) when interacting with external data sources, particularly in scenarios involving numerous API calls and large datasets. Current research emphasizes techniques like prompt engineering to enable LLMs to autonomously manage data caching, thereby reducing computational overhead and improving response times. This work is significant because it addresses a critical scalability bottleneck for LLMs, paving the way for more efficient and practical applications in areas such as personalized recommendations, named entity recognition, and robotic task planning.