LLMs or Naive Bayes? Old Gems or New Ways
Benchmarking classical probability models against state-of-the-art LLMs in real-world classification tasks.
Large language models (LLMs) prompt a recurring question in research computing: should classical methods like Naive Bayes (NB) be retired? We benchmark Complement Naive Bayes against zero-shot and few-shot LLMs spanning four model families and a 37x range in scale (27B to a 1T-pa...
ArXiv CS.LG
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This research demonstrates that classical algorithms like Naive Bayes remain highly competitive for specific classification tasks where computational efficiency is paramount. By highlighting where simple models outperform massive neural networks, the study encourages a more pragmatic, resource-conscious approach to AI architecture selection.
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