On the Hallucination in Simultaneous Machine Translation
Zhong, Meizhi, Chen, Kehai, Xue, Zhengshan, Liu, Lemao, Yang, Mingming, Zhang, Min
–arXiv.org Artificial Intelligence
It is widely known that hallucination is a critical issue in Simultaneous Machine Translation (SiMT) due to the absence of source-side information. While many efforts have been made to enhance performance for SiMT, few of them attempt to understand and analyze hallucination in SiMT. Therefore, we conduct a comprehensive analysis of hallucination in SiMT from two perspectives: understanding the distribution of hallucination words and the target-side context usage of them. Intensive experiments demonstrate some valuable findings and particularly show that it is possible to alleviate hallucination by decreasing the over usage of target-side information for SiMT.
arXiv.org Artificial Intelligence
Jun-11-2024
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- Research Report > New Finding (0.68)
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