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Revolutionizing Positional Encoding for Language Models
This chapter explores the novel method of contextual positional encoding (COPE) that enhances traditional transformer models in language processing. It highlights the limitations of existing models and showcases how COPE enables better context management and improved performance in tasks requiring counting and logical reasoning.
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