An LLM-based pipeline turns 20 years of PNAS engineering abstracts into sixteen interpretable topics and maps cross-topic links from full text, claiming to rediscover the journal's own dual-classification structure.
Lay summaries needed to enhance science communication.Proceedings of the National Academy of Sciences, 112(12):3585–3586, 2015
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Mapping Scientific Literature with Large Language Models and Topic Modeling
An LLM-based pipeline turns 20 years of PNAS engineering abstracts into sixteen interpretable topics and maps cross-topic links from full text, claiming to rediscover the journal's own dual-classification structure.