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
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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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Rotary Position Embedding (RoPE) introduced in paper: RoFormer: Enhanced Transformer with Rotary Position Embedding (Su et al., 2021). — SourceScore Claim f8d64457ba9fd35b (verified 2026-05-16). https://sourcescore.org/api/v1/claims/f8d64457ba9fd35b.jsonEmbed this claim
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Frequently asked questions
Is the claim "Rotary Position Embedding (RoPE) introduced in paper: RoFormer: Enhanced Transformer with Rotary Position Embedding (Su et al., 2021)." verified?
Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
What is the evidence for "Rotary Position Embedding (RoPE) introduced in paper: RoFormer: Enhanced Transformer with Rotary Position Embedding (Su et al., 2021)."?
Evidence comes from 2 primary sources: arXiv (Su, Lu, Pan, Murtadha, Wen, Liu), Zhuiyi Technology. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/f8d64457ba9fd35b.json includes an HMAC-SHA256 signature for audit verification.
When was this claim last verified by SourceScore?
Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.
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cURL
curl https://sourcescore.org/api/v1/claims/f8d64457ba9fd35b.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/f8d64457ba9fd35b.json");
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// "Rotary Position Embedding (RoPE) introduced in paper: RoFormer: Enhanced Transformer with Rotary Position Embedding (Su et al., 2021)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/f8d64457ba9fd35b.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Rotary Position Embedding (RoPE) introduced in paper: RoFormer: Enhanced Transformer with Rotary Position Embedding (Su et al., 2021)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_rotary_position_embedding_rope_fact() -> dict:
"""Fetch the verified SourceScore claim for Rotary Position Embedding (RoPE)."""
r = httpx.get("https://sourcescore.org/api/v1/claims/f8d64457ba9fd35b.json")
return r.json()