AcawebAgent: A Large Language Model-Powered Assistant for Early Academic Research

The rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies, particularly in large language models (LLMs) like the GPT series, has significantly impacted research and industrial applications. These models excel in various natural language processing (NLP) tasks, including text generation, comprehension, and translation. However, harnessing these capabilities for academic research still presents challenges, particularly for early-career researchers navigating extensive literature. In this paper, we introduce AcawebAgent, an inventive AutoAgent specifically crafted to enhance the abilities of beginner researchers. It leverages the advanced generation and analysis capabilities of large language models (LLMs) to collect open academic knowledge from the web. AcawebAgent offers customized research reports that include in-depth overviews, practical applications, the latest developments, and future trajectories of specific research domains, thereby significantly diminishing the time and effort needed for comprehensive literature reviews and trend analyses.