On the Information Redundancy in Non-Autoregressive Translation
<|reference_start|>On the Information Redundancy in Non-Autoregressive Translation: 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.<|reference_end|>
@article{wang2024on,
    title={On the Information Redundancy in Non-Autoregressive Translation},
    author={Zhihao Wang, Longyue Wang, Jinsong Su, Junfeng Yao, Zhaopeng Tu},
    journal={arXiv preprint arXiv:2405.02673},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.02673},
    primaryClass={cs.CL}
}