Enhanced Hallucination Detection in Neural Machine Translation through Simple Detector Aggregation

arXiv:2402.13331v1 Announce Type: new
Abstract: Hallucinated translations pose significant threats and safety concerns when it comes to the practical deployment of machine translation systems. Previous research works have identified that detectors exhibit complementary performance different detectors excel at detecting different types of hallucinations. In this paper, we propose to address the limitations of individual detectors by combining them and introducing a straightforward method for aggregating multiple detectors. Our results demonstrate the efficacy of our aggregated detector, providing a promising step …

abstract aggregation arxiv concerns cs.cl deployment detection excel hallucination hallucinations machine machine translation neural machine translation paper performance practical research safety simple systems threats through translation type types