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What LLMs Do in the Shadows: Reading Context Reliance from the Unembedding Dark Space
Detecting faithfulness hallucinations in large language models (LLMs) is crucial for their safe deployment in high-stakes domains. Recent approaches address this by contrasting contextual against parametric knowledge utilization, yet measuring context reliance typically demands noticeable overhead,
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