Lightweight LLMs reach competitive performance on biomedical named entity recognition with select output formats, while instruction tuning across many formats shows no benefit.
In this setting, structured prediction plays a central role as it enables models to generate outputs with predefined structures
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Analysing Lightweight Large Language Models for Biomedical Named Entity Recognition on Diverse Ouput Formats
Lightweight LLMs reach competitive performance on biomedical named entity recognition with select output formats, while instruction tuning across many formats shows no benefit.