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SurveyAgent-HKA: A multi-agent framework for scientific survey generation with LLMs and human knowledge augmentation

arXiv · AI, language, vision and robotics · article · Sep 5, 2026 · UTC

Automatic scientific survey generation has become an important task in scientific document processing. The common approach of retrieving literature from a single source (e.g., arXiv) and generating surveys through a one-pass large language model (LLM) call often leads to limited reference coverage and, more importantly, fails to replicate the expert-driven revision process that is crucial for writing high-quality surveys. In this paper, we introduce SurveyAgent-HKA, a multi-agent framework that improves end-to-end scientific survey generation by incorporating knowledge derived from published s

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