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Federico Barbero

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12:53
2026-09-10
arxiv.org
large-language-models

What Makes Rotary Positional Encodings Useful?

A paper by Federico Barbero and co-authors, revised 13 May 2025 as v3 on arXiv, argues that Rotary Positional Encodings (RoPE) in Transformer-based large language models are not primarily useful for dā€¦

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Gemma 7B 1 arXiv 1 Rotary Positional Encodings 1 Transformer 1
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large language models 1 ai research 1 natural language processing 1 machine learning 1