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As a novel AI-powered conversational system, large language models (LLMs) have the potential to be used in various applications. Recent advances in LLMs like ChatGPT have made LLM-based academic tools possible. However, most of the existing studies on the adoption of LLM for academic tasks were based on theoretical or qualitative analyses, which failed to provide empirical evidence on the effects of LLMs on users’ behaviors. Additionally, although previous work has investigated users’ acceptance of conventional conversational systems, little is known about how scholars evaluate LLMs when they are used for academic tasks. Hence, we conducted an empirical field experiment to assess the performance of 48 early-stage scholars on two core academic activities (paper reading and literature reviews) under varying time constraints. Prior to the tasks, participants underwent different training programs …