SubmissionNumber#=%=#68
FinalPaperTitle#=%=#CRCL at SemEval-2024 Task 2: Simple prompt optimizations
ShortPaperTitle#=%=#
NumberOfPages#=%=#6
CopyrightSigned#=%=#ClementBM
JobTitle#==#
Organization#==#CRCL
Abstract#==#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
Author{1}{Firstname}#=%=#Clement
Author{1}{Lastname}#=%=#Brutti-Mairesse
Author{1}{Username}#=%=#clementbm
Author{1}{Email}#=%=#clement.bruttimairesse@lyon.unicancer.fr
Author{1}{Affiliation}#=%=#CRCL

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