Prabhu, M.M.Srinivasa, H.Anand Kumar, M.2026-02-062024SemEval 2024 - 18th International Workshop on Semantic Evaluation, Proceedings of the Workshop, 2024, Vol., , p. 193-199https://doi.org/10.18653/v1/2024.semeval-1.30https://idr.nitk.ac.in/handle/123456789/28797This paper summarizes Team SCaLAR's work on SemEval-2024 Task 5: Legal Argument Reasoning in Civil Procedure. To address this Binary Classification task, which was daunting due to the complexity of the Legal Texts involved, we propose a simple yet novel similarity and distance-based unsupervised approach to generate labels. Further, we explore the Multi-level fusion of Legal-Bert embeddings using ensemble features, including CNN, GRU and LSTM. To address the lengthy nature of Legal explanation in the dataset, we introduce T5-based segment-wise summarization, which successfully retained crucial information, enhancing the model's performance. Our unsupervised system witnessed a 20-point increase in macro F1-score on the development set and a 10-point increase on the test set, which is promising given its uncomplicated architecture. © 2024 Association for Computational Linguistics.