<ul><li>This article is part of a broader study. You’re reading Part 4 of 9.</li><li>LLMs training, evaluation, and inference: The article discusses the training and evaluation process of LLMs (Language Models) for extracting entities and relationships from scientific papers.</li><li>Fine-tuned LLM: The article highlights the use of a fine-tuned LLM that demonstrates optimal performance in both Named Entity Recognition (NER) and Relation Extraction (RE) tasks.</li><li>Enhancing data integrity: The fine-tuned LLM not only extracts entities and assigns labels but also ensures traceability, enhancing the integrity and utility of the data.</li></ul>

This AI Doesn’t Just Skim Scientific Papers—It Tags, Sorts, and Explains Them Too

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