NLP At UC Santa Cruz At Semeval-2024 Task 5: Legal Answer Validation Using Few-shot Multi-choice QA

Pahilajani Anish, Jain Samyak Rajesh, Trivedi Devasha. Arxiv 2024

[Paper]    
BERT Few Shot GPT In Context Learning Model Architecture Prompting

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.

Similar Work