AILS-NTUA at SemEval-2025 Task 3: Leveraging Large Language Models and Translation Strategies for Multilingual Hallucination Detection

Dimitra Karkani, Maria Lymperaiou, Giorgos Filandrianos, Nikolaos Spanos, Athanasios Voulodimos +1 more
3/4/2025
cs.CL

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Abstract

Multilingual hallucination detection stands as an underexplored challenge, which the Mu-SHROOM shared task seeks to address. In this work, we propose an efficient, training-free LLM prompting strategy that enhances detection by translating multilingual text spans into English. Our approach achieves competitive rankings across multiple languages, securing two first positions in low-resource languages. The consistency of our results highlights the effectiveness of our translation strategy for hallucination detection, demonstrating its applicability regardless of the source language.

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Cite this paper

@article{karkani2025ailsntua,
  title  = {AILS-NTUA at SemEval-2025 Task 3: Leveraging Large Language Models and Translation Strategies for Multilingual Hallucination Detection},
  author = {Dimitra Karkani and Maria Lymperaiou and Giorgos Filandrianos and Nikolaos Spanos and Athanasios Voulodimos and Giorgos Stamou},
  year   = {2025},
  eprint = {2503.02442},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.02442v1}
}

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