Unverified50% confidenceFactExact time
The Transformer architecture, contrastive learning, and reinforcement learning with human feedback (RLHF) are paradigm-level innovations.
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50%
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Long-term
Relevance
10/10/2026
First Seen
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Unverified大模型核心原理包括Transformer架构、预训练、SFT监督微调、RLHF人类反馈强化学习等关键概念77% similarUnverifiedRWKV将RNN的线性推理效率与Transformer的并行训练能力融合77% similarUnverified学习Transformer应遵循'先建立问题意识，再引入解决方案'的四阶段路径：序列建模动机、RNN/LSTM及其局限、注意力机制、Transformer完整架构75% similarVerifiedInstruction fine-tuning was systematically proposed by InstructGPT (2022), combining reinforcement learning from human feedback (RLHF) to make models better aligned with human intent.71% similar
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