title: Why Are Positional Encodings Nonessential for Deep Autoregressive Transformers? Revisiting a Petroglyph
abstract: Do autoregressive Transformer language models require explicit positional encodings (PEs)? The answer is 'no' provided they have more than one layer -- they can distinguish sequences with permuted tokens without the need for explicit PEs. This follows from the fact that a cascade of (permutation invariant) set processors can collectively exhibit sequence-sensitive behavior in the autoregressive setting. This property has been known since early efforts (contemporary with GPT-2) adopting the Trans
journal: arXiv (Cornell University)