Using TabPFNv2 on compressed LLM hidden states and attention lookback features detects RAG hallucinations with 250 training samples at levels near GPT-4o-based judges, though clearly below them on EManual.
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Data-efficient Meta-models for Evaluation of Context-based Questions and Answers in LLMs
Using TabPFNv2 on compressed LLM hidden states and attention lookback features detects RAG hallucinations with 250 training samples at levels near GPT-4o-based judges, though clearly below them on EManual.