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This study presents a comparative analysis of automatic text classification approaches in the legal domain, focusing on performance, energy consumption, and costs. It evaluates traditional SVM-based models against recent large language models (LLMs) and generative models using the LexGLUE benchmark, revealing that simpler algorithms can achieve similar performance with significantly lower energy consumption and costs. The findings emphasize the need for companies and researchers to consider energy efficienc

Author

Darren

Language

EN