When Ground Truth Is Not Ground Truth: Automatic Labeling for Hallucination Detection
Hallucinations in Large Language Models (LLMs) remain a major challenge, as they can produce misleading, factually incorrect, or unverifiable information, thereby undermining their trustworthiness and reliability. However, reliable ground-truth labels remain a key challenge in evaluating hallucination detectors. Recent...
Rounak Sen, Divya Kumari, Deeksha Varshney
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