Closed Source Large Language Model

Closed-source large language models (LLMs) are powerful AI systems whose inner workings are not publicly accessible, limiting researchers' ability to fully understand and improve them. Current research focuses on mitigating the limitations of this closed nature by exploring methods like instruction tuning with data generated from open-source LLMs, developing techniques to evaluate and enhance their performance (e.g., through prompt optimization and meta-ranking), and addressing safety concerns such as jailbreaking and bias. This research is crucial for advancing the field, enabling more responsible development and deployment of LLMs across various applications while also fostering the development of more transparent and accessible alternatives.