ANHALTEN: Cross-Lingual Transfer for German Token-Level Reference-Free Hallucination Detection

• URL: http://arxiv.org/abs/2407.13702v1
• Date: Thu, 18 Jul 2024 17:01:38 GMT
• Title: ANHALTEN: Cross-Lingual Transfer for German Token-Level Reference-Free Hallucination Detection
• Authors: Janek Herrlein, Chia-Chien Hung, Goran Glavaš,
• Abstract summary: We introduce ANHALTEN, a dataset that extends the English hallucination detection dataset to German. This is the first work that explores cross-lingual transfer for token-level reference-free hallucination detection. We show that the sample-efficient few-shot transfer is the most effective approach in most setups.
• Score: 3.1269598124014264
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Research on token-level reference-free hallucination detection has predominantly focused on English, primarily due to the scarcity of robust datasets in other languages. This has hindered systematic investigations into the effectiveness of cross-lingual transfer for this important NLP application. To address this gap, we introduce ANHALTEN, a new evaluation dataset that extends the English hallucination detection dataset to German. To the best of our knowledge, this is the first work that explores cross-lingual transfer for token-level reference-free hallucination detection. ANHALTEN contains gold annotations in German that are parallel (i.e., directly comparable to the original English instances). We benchmark several prominent cross-lingual transfer approaches, demonstrating that larger context length leads to better hallucination detection in German, even without succeeding context. Importantly, we show that the sample-efficient few-shot transfer is the most effective approach in most setups. This highlights the practical benefits of minimal annotation effort in the target language for reference-free hallucination detection. Aiming to catalyze future research on cross-lingual token-level reference-free hallucination detection, we make ANHALTEN publicly available: https://github.com/janekh24/anhalten

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