Understanding the role of human preferences in LLM evaluation
The evaluation of language models could significantly benefit from the introduction of automated systems that incorporate human preferences. These systems aim to enhance the accuracy and efficiency of evaluating large language models (LLMs) by applying machine learning algorithms. By integrating human decision-making aspects, the evaluations can become more aligned with actual human use and expectations. This integration of human preferences has the potential not only to optimize LLMs for more practical applications but also to streamline the cumbersome evaluation process, making it a key consideration for future developments in the field.
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OpenAI
](https://go.kolena.com/human-preferences-for-llm-evaluation)