New Paper Proposes Detecting LLM Hallucinations via Feed-Forward Neurons

A preprint introduces NeuroActiSep, a method that aims to spot factual hallucinations in large language models by inspecting feed-forward neurons, according to its abstract. The approach is described as working in a single pass, making it cheaper than methods requiring repeated sampling. The paper frames this as an under-explored alternative to existing white-box truthfulness detection techniques.