Researcher profile
Federico Barbero
1 paper in the PaperMetrix corpus
Publications
Papers by this author
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Round and Round We Go! What makes Rotary Positional Encodings useful?
2024 · arXiv (Cornell University)
Positional Encodings (PEs) are a critical component of Transformer-based Large Language Models (LLMs), providing the attention mechanism with important sequence-position information. One of the most popular types of encoding used today in LLMs are Rotary …