Positional Embedding — 3 Technical Articles

Feb 4, 2026 · Artificial Intelligence

How Sakana AI Redefines Long-Context Transformers: DroPE, REPO, and FwPKM Explained

This article analyzes Sakana AI's three recent papers that challenge traditional Transformer long‑sequence handling by removing positional embeddings, reconstructing position awareness, and adding a fast‑weight external memory, showing how each approach improves ultra‑long text understanding.

Memory MechanismPositional EmbeddingTransformer

0 likes · 12 min read

How Sakana AI Redefines Long-Context Transformers: DroPE, REPO, and FwPKM Explained

AI Large Model Application Practice

Jan 15, 2026 · Artificial Intelligence

Why Transformers Need Positional Embeddings and How They Work

This article explains the order‑blindness of Transformer self‑attention, why naïvely adding raw position indices harms semantics, and walks through sinusoidal, learnable, and rotary positional encodings together with PI and YaRN techniques for extending sequence length.

AILLMPositional Embedding

0 likes · 12 min read

Why Transformers Need Positional Embeddings and How They Work

Huawei Cloud Developer Alliance

Oct 25, 2023 · Artificial Intelligence

Unlocking GLM & ChatGLM: Deep Dive into MindSpore Large‑Model Techniques

The MindSpore Season 2 open class offers a comprehensive overview of GLM to ChatGLM architectures, positional‑embedding strategies, stable training optimizations, and step‑by‑step instructions for deploying large language models with Ascend, ModelArts, and MindSpore Transformers, while previewing upcoming multimodal remote‑sensing sessions.

Artificial IntelligenceChatGLMGLM

0 likes · 6 min read

Unlocking GLM & ChatGLM: Deep Dive into MindSpore Large‑Model Techniques