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, such as materializin...
A. Kuleshova, Andrey Volodichev, Daria Kotova et al.
· 0 citations