Papers with LLMs)—characterized

1 papers
Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization (2026.findings-acl)

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Challenge: Hallucinations in Large Language Models persist in critical domains where generated content diverges from contextual facts or logical constraints.
Approach: They propose to generate hallucinations as orthogonal noise relative to the semantic manifold of the residual stream.
Outcome: The proposed method achieves superior contextual faithfulness compared to state-of-the-art methods.

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