GPT-2

This article systematically reviews how large language models encode and process token position information, covering classic approaches through contemporary methods such as RoPE, with visual examples, math, and a small PyTorch implementation. It also compares positional encoding choices across 2026 open-weight models and examines how modern architectures adapt or omit explicit positional encodings.