> ...proving that this one particular piece of the hallucination problem may be conceptually simple.
Everything mentioned in the article boils down to that one particular piece-- non-detected uncertainty. The architecture constraints referenced are all situations that cause uncertainty. Training data gaps of course increase uncertainty.
Their solutions are a shotgun blast of heuristics that all focus on reducing uncertainty-- CoT, RAG, fine-tuning, fact-checking -- while somehow avoiding actually measuring uncertainty and using that to eliminate hallucinations!
Everything mentioned in the article boils down to that one particular piece-- non-detected uncertainty. The architecture constraints referenced are all situations that cause uncertainty. Training data gaps of course increase uncertainty.
Their solutions are a shotgun blast of heuristics that all focus on reducing uncertainty-- CoT, RAG, fine-tuning, fact-checking -- while somehow avoiding actually measuring uncertainty and using that to eliminate hallucinations!