Geometric Taxonomy of LLM Hallucinations

What Changed

Taxonomy identifies unfaithfulness, confabulation, and factual error with distinct embedding signatures.

Why It Matters

This clarifies embedding-based detection limits, pushing for hybrid methods combining geometry with external fact-checking. It explains why some hallucinations evade current safeguards, aiding safer LLM deployment.

What To Do Next

Compute discriminative directions in embedding space to detect confabulations on your LLM outputs.