"You can measure how far a new example sits from familiar ones to help detect out-of-distribution inputs."
Liu and colleagues evaluated OOD detection techniques on LLaMA language models and found strong results from a simple cosine-distance detector. Their experiments directly support using distances in learned representation spaces to identify unfamiliar inputs in LLM applications.
View Source