Papers by Valerii Olisov

1 papers
When Models Lie, We Learn: Multilingual Span-Level Hallucination Detection with PsiloQA (2025.findings-emnlp)

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Challenge: Existing hallucination detection benchmarks operate at the sequence level and are limited to English . Existing methods lacking fine-grained, multilingual supervision are limited in English based on the sequence .
Approach: They propose a large-scale, multilingual dataset annotated with span-level hallucinations across 14 languages.
Outcome: The proposed dataset annotated with span-level hallucinations across 14 languages is scalable and cost-efficient.

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