  We present a baseline for the SemEval 2024 task 2 challenge, whose objective
is to ascertain the inference relationship between pairs of clinical trial
report sections and statements. We apply prompt optimization techniques with
LLM Instruct models provided as a Language Model-as-a-Service (LMaaS). We
observed, in line with recent findings, that synthetic CoT prompts
significantly enhance manually crafted ones.
