LLM Based Pipeline

LLM-based pipelines are designed to leverage the capabilities of large language models (LLMs) for complex tasks by chaining together multiple LLM calls or integrating them with other components. Current research focuses on improving pipeline design through techniques like combinatorial optimization to enhance solution quality, developing user-friendly interfaces for creating and evaluating these pipelines, and addressing challenges such as context length limitations and the need for efficient knowledge transfer between different sized LLMs. These pipelines are being applied across diverse domains, including legal, medical, and scientific literature review, with the goal of improving accuracy, efficiency, and accessibility of LLM applications in various fields.