Revisiting the Markov Property for Machine Translation
<|reference_start|>Revisiting the Markov Property for Machine Translation: In this paper, we re-examine the Markov property in the context of neural machine translation. We design a Markov Autoregressive Transformer~(MAT) and undertake a comprehensive assessment of its performance across four WMT benchmarks. Our findings indicate that MAT with an order larger than 4 can generate translations with quality on par with that of conventional autoregressive transformers. In addition, counter-intuitively, we also find that the advantages of utilizing a higher-order MAT do not specifically contribute to the translation of longer sentences.<|reference_end|>
@article{du2024revisiting,
    title={Revisiting the Markov Property for Machine Translation},
    author={Cunxiao Du, Hao Zhou, Zhaopeng Tu, Jing Jiang},
    journal={arXiv preprint arXiv:2402.02084},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.02084},
    primaryClass={cs.CL}
}