Pairwise Evaluations with LangSmith

Pairwise evaluation is a method used to teach large language models (LLMs) human preference by presenting them with pairs of candidate answers and allowing them to choose the better one. This approach has gained popularity in benchmarking LLM model performance, particularly in tasks like chat or writing where there may not be a single correct answer. LangSmith, an AI platform for developing and testing LLM applications, has added pairwise evaluation as a new feature to help users improve their LLM applications. By defining custom pairwise evaluators and comparing two LLM generations using these evaluators, developers can gain insights into model performance and make informed decisions about which models to use in their applications.