Clement Brutti-mairesse

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2024

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CRCL at SemEval-2024 Task 2: Simple prompt optimizations
Clement Brutti-mairesse | Loic Verlingue
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)

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.The source code is available at this GitHub repository https://github.com/ClementBM-CLB/semeval-2024
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