Verified65% confidenceFactExact time
RoPE (Rotary Position Embedding) was proposed by Su Jianlin in 2021 and has become standard in mainstream models such as LLaMA, Qwen, and Mistral.
3
Sources
65%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
15岁少年从零训练200M MoE语言模型：完整架构与实战拆解
redditr/learnmachinelearning7/12/2026
Related Claims
UnverifiedRoPE is the positional encoding scheme used by current mainstream large models, proposed by Su Jianlin in 2021.76% similarUnverifiedLLaVA proposed a minimalist three-stage paradigm of visual encoder + projection layer + LLM in 2023, which was inherited by subsequent works such as InternVL and Qwen-VL.66% similarUnverifiedSince 2024, models such as Trellis, Hunyuan3D, and Meshy have begun to support the direct generation of mesh models with high-quality textures and standard topology.64% similarUnverifiedThe first-generation Qwen was released in August 2023, based on the standard Transformer architecture, employing RoPE, pre-layer RMS Norm, and SwiGLU activation functions, with bias terms removed from most linear layers.64% similarUnverifiedAs of 2025, llama.cpp supports dozens of model architectures including Qwen, DeepSeek, Mistral, and Gemma.63% similar
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