Prefill Awareness study probes what LLMs know before decoding

A new arXiv paper examines prefill awareness in large language models.

The prefill stage is where a model processes the prompt before generating new tokens. Understanding what the model represents at that point can clarify how context is used and where inference-time behavior comes from.

For practitioners, this kind of work matters because serving optimizations, long-context behavior, and agent reliability all depend on how models handle context before decoding begins.