#Transformer

2026

• 06-12 EN

  SliceGPT: Post-Training LLM Compression via Computational Invariance

• 06-12 中

  SliceGPT 阅读笔记：用计算不变性删除 Transformer 的行与列

• 06-11 EN

  MegaScale: Engineering 55% MFU at 12,288 GPUs for LLM Training

• 06-11 中

  MegaScale：ByteDance 如何在 12,288 块 GPU 上实现 55% MFU 的大规模 LLM 训练

• 04-22 EN

  SAGE: Training-Free Semantic Evidence Composition for Edge-Cloud Inference Under Hard Uplink Budgets

• 03-28 EN

  Mamba: Linear-Time Sequence Modeling with Selective State Spaces — In-Depth Technical Review

• 03-22 EN

  Attention Is All You Need: The Transformer — In-Depth Technical Review

• 02-18 EN

  DeepSeek-V2: Multi-head Latent Attention and DeepSeekMoE — Technical Review

• 02-18 EN

  GLM-5 Technical Review: From Vibe Coding to Agentic Engineering