Assessing and Verifying Task Utility in LLM-Powered Applications

arXiv:2405.02178v1 Announce Type: new
Abstract: The rapid development of Large Language Models (LLMs) has led to a surge in applications that facilitate collaboration among multiple agents, assisting humans in their daily tasks. However, a significant gap remains in assessing to what extent LLM-powered applications genuinely enhance user experience and task execution efficiency. This highlights the need to verify utility of LLM-powered applications, particularly by ensuring alignment between the application's functionality and end-user needs. We introduce AgentEval, a novel framework designed …

applications arxiv cs.ai cs.cl llm type utility