Beyond Metrics: A Critical Analysis of the Variability in Large Language Model Evaluation Frameworks

التفاصيل البيبلوغرافية
العنوان: Beyond Metrics: A Critical Analysis of the Variability in Large Language Model Evaluation Frameworks
المؤلفون: Pimentel, Marco AF, Christophe, Clément, Raha, Tathagata, Munjal, Prateek, Kanithi, Praveen K, Khan, Shadab
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Artificial Intelligence, Computer Science - Computation and Language
الوصف: As large language models (LLMs) continue to evolve, the need for robust and standardized evaluation benchmarks becomes paramount. Evaluating the performance of these models is a complex challenge that requires careful consideration of various linguistic tasks, model architectures, and benchmarking methodologies. In recent years, various frameworks have emerged as noteworthy contributions to the field, offering comprehensive evaluation tests and benchmarks for assessing the capabilities of LLMs across diverse domains. This paper provides an exploration and critical analysis of some of these evaluation methodologies, shedding light on their strengths, limitations, and impact on advancing the state-of-the-art in natural language processing.
Comment: 15 pages, 3 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2407.21072
رقم الأكسشن: edsarx.2407.21072
قاعدة البيانات: arXiv