Large Language Models and Prompt Engineering for Biomedical Query
  Focused Multi-Document Summarisation
Diego Mollá
This paper reports on the use of prompt engineering and GPT-3.5 for
biomedical query-focused multi-document summarisation. Using GPT-3.5 and
appropriate prompts, our system achieves top ROUGE-F1 results in the task of
obtaining short-paragraph-sized answers to biomedical questions in the 2023
BioASQ Challenge (BioASQ 11b). This paper confirms what has been observed in
other domains: 1) Prompts that incorporated few-shot samples generally improved
on their counterpart zero-shot variants; 2) The largest improvement was
achieved by retrieval augmented generation. The fact that these prompts allow
our top runs to rank within the top two runs of BioASQ 11b demonstrate the
power of using adequate prompts for Large Language Models in general, and
GPT-3.5 in particular, for query-focused summarisation.