On the Information Redundancy in Non-Autoregressive Translation

• URL: http://arxiv.org/abs/2405.02673v1
• Date: Sat, 4 May 2024 14:20:28 GMT
• Title: On the Information Redundancy in Non-Autoregressive Translation
• Authors: Zhihao Wang, Longyue Wang, Jinsong Su, Junfeng Yao, Zhaopeng Tu,
• Abstract summary: Token repetition is a typical form of multi-modal problem in non-autoregressive translation (NAT) In this work, we revisit the multi-modal problem in recently proposed NAT models. We identify two types of information redundancy errors that correspond well to lexical and reordering multi-modality problems.
• Score: 82.43992805551498
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Token repetition is a typical form of multi-modal problem in fully non-autoregressive translation (NAT). In this work, we revisit the multi-modal problem in recently proposed NAT models. Our study reveals that these advanced models have introduced other types of information redundancy errors, which cannot be measured by the conventional metric - the continuous repetition ratio. By manually annotating the NAT outputs, we identify two types of information redundancy errors that correspond well to lexical and reordering multi-modality problems. Since human annotation is time-consuming and labor-intensive, we propose automatic metrics to evaluate the two types of redundant errors. Our metrics allow future studies to evaluate new methods and gain a more comprehensive understanding of their effectiveness.

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