这期视频用最最最最通俗的语言给大家描绘了下大模型架构的演进历程,希望大家喜欢并且有帮助!
PE: https://arxiv.org/abs/1706.03762v7
RoPE: https://arxiv.org/abs/2104.09864
NoPE: https://arxiv.org/abs/2305.19466
YaRN: https://arxiv.org/abs/2309.00071
LayerNorm: https://arxiv.org/abs/1607.06450
RMSNorm: https://arxiv.org/abs/1910.07467
QKNorm / KVNorm: https://arxiv.org/abs/2010.04245
Pre-Norm / Post-Norm: https://arxiv.org/abs/2002.04745
MHA: https://arxiv.org/abs/1706.03762v7
MQA: https://arxiv.org/abs/1911.02150
GQA: https://arxiv.org/abs/2305.13245
MLA: https://arxiv.org/abs/2405.04434
Sparse Transformer: https://arxiv.org/abs/1904.10509
DSA: https://arxiv.org/abs/2512.02556
SWA: https://arxiv.org/abs/2004.05150
Gemma2 使用 SWA: https://arxiv.org/abs/2408.00118
CSA / HCA: https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro/blob/main/DeepSeek_V4.pdf
KDA: https://arxiv.org/abs/2510.26692
Gated DeltaNet: https://arxiv.org/abs/2412.06464
Lightning Attention: https://arxiv.org/abs/2401.04658
Mamba: https://arxiv.org/abs/2312.00752
Mamba-2: https://arxiv.org/abs/2405.21060
Mamba-3: https://arxiv.org/abs/2603.15569
MoE: https://arxiv.org/abs/1701.06538
Switch Transformer: https://arxiv.org/abs/2101.03961
DeepSeekMoE: https://arxiv.org/abs/2401.06066
GELU: https://arxiv.org/abs/1606.08415
SiLU: https://arxiv.org/abs/1702.03118
Swish: https://arxiv.org/abs/1710.05941v1
RC: https://arxiv.org/abs/1512.03385
HC: https://arxiv.org/abs/2409.19606
mHC: https://arxiv.org/abs/2512.24880
AttnResidual: https://arxiv.org/abs/2603.15031