SubmissionNumber#=%=#198
FinalPaperTitle#=%=#NLP at UC Santa Cruz at SemEval-2024 Task 5: Legal Answer Validation using Few-Shot Multi-Choice QA
ShortPaperTitle#=%=#
NumberOfPages#=%=#6
CopyrightSigned#=%=#Devasha Trivedi
JobTitle#==#
Organization#==#
Abstract#==#This paper presents our submission to the SemEval 2024 Task 5: The Legal Argument Reasoning Task in Civil Procedure. We present two approaches to solving the task of legal answer validation, given an introduction to the case, a question and an answer candidate. Firstly, we fine-tuned pre-trained BERT-based models and found that models trained on domain knowledge perform better. Secondly, we performed few-shot prompting on GPT models and found that reformulating the answer validation task to be a multiple-choice QA task remarkably improves the performance of the model. Our best submission is a BERT-based model that achieved the 7th place out of 20.
Author{1}{Firstname}#=%=#Anish
Author{1}{Lastname}#=%=#Pahilajani
Author{1}{Email}#=%=#apahilaj@ucsc.edu
Author{1}{Affiliation}#=%=#UC Santa Cruz
Author{2}{Firstname}#=%=#Samyak Rajesh
Author{2}{Lastname}#=%=#Jain
Author{2}{Email}#=%=#srajeshj@ucsc.edu
Author{2}{Affiliation}#=%=#UC Santa Cruz
Author{3}{Firstname}#=%=#Devasha
Author{3}{Lastname}#=%=#Trivedi
Author{3}{Username}#=%=#devashatrivedi
Author{3}{Email}#=%=#detrived@ucsc.edu
Author{3}{Affiliation}#=%=#UC Santa Cruz

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