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20222025
most citedA Comparison Between Tsetlin Machines and Deep Neural Networks in the Context of Recommendation Systems

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cs.CL2025

English K_Quantization of LLMs Does Not Disproportionately Diminish Multilingual Performance

Karl Audun Borgersen, Morten Goodwin

For consumer usage of locally deployed LLMs, the GGUF format and k\_quantization are invaluable tools for maintaining the performance of the original model while reducing it to siz…