HalluTruthQA-4K: A Fine-Grained Corpus and Annotation Process for Arabic Hallucination Detection and Truth Verification
arXiv · · Significant research
Summary
Researchers introduced HalluTruthQA-4K, an expanded corpus comprising 4,000 expert-curated Arabic question-answering instances designed for hallucination detection and truth verification. This resource spans four knowledge-intensive domains: Islamic knowledge, history, science, and geography, and serves as the official dataset for Track 2 of the HalluScoring 2026 shared task. For hallucinated responses, the corpus provides character-level erroneous spans, human-written explanations, and hierarchical hallucination types, alongside verified reference answers and distractors. Why it matters: HalluTruthQA-4K provides a crucial fine-grained resource for evaluating and improving the factual reliability and trustworthiness of Arabic large language models.
Keywords
HalluTruthQA-4K · Hallucination detection · Factual verification · Arabic language models · Dataset
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