Verified claim · AI-ML · 100% confidence
Rotary Position Embedding (RoPE) introduced in paper: RoFormer: Enhanced Transformer with Rotary Position Embedding (Su et al., 2021).
Last verified 2026-05-16 · Methodology veritas-v0.1 · f8d64457ba9fd35b
Structured fields
- Subject
- Rotary Position Embedding (RoPE)
- Predicate
introduced_in_paper- Object
- RoFormer: Enhanced Transformer with Rotary Position Embedding (Su et al., 2021)
- Confidence
- 100%
- Tags
- rope · position-embedding · transformer · foundational · 2021
Sources (2)
[1] preprint · arXiv (Su, Lu, Pan, Murtadha, Wen, Liu) · 2021-04-20
RoFormer: Enhanced Transformer with Rotary Position Embedding“In this paper, we first investigate various methods to integrate positional information into the learning process of transformer-based language models. Then, we propose a novel method named Rotary Position Embedding (RoPE) to effectively leverage the positional information.”
[2] github release · Zhuiyi Technology · 2021-04-20
ZhuiyiTechnology/roformer — official implementation
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