@inproceedings{rui-etal-2024-rong,
title = "融合确定性因子及区域密度的k-最近邻机器翻译方法(A k-Nearest-Neighbor Machine Translation Method Combining Certainty Factor and Region Density)",
author = "Qi, Rui and
Shi, Xiangyu and
Man, Zhibo and
Xu, Jinan and
Chen, Yufeng",
editor = "Maosong, Sun and
Jiye, Liang and
Xianpei, Han and
Zhiyuan, Liu and
Yulan, He",
booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)",
month = jul,
year = "2024",
address = "Taiyuan, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2024.ccl-1.16/",
pages = "217--229",
language = "zho",
abstract = "``k-最近邻机器翻译(kNN-MT)是近年来神经机器翻译领域的一个重要研究方向。此类方法可以在不更新机器翻译模型的情况下提高翻译质量,但训练数据中高低频单词的数量不均衡限制了模型效果,且固定的k值无法对处于不同密度分布的数据都产生良好的翻译结果。为此本文提出了一种创新的kNN-MT方法,引入确定性因子(CF)来降低数据不均衡对模型效果的影响,并根据测试点周边数据密度动态选择k值。在多领域德-英翻译数据集上,相比基线实验,本方法在四个领域上翻译效果均有提升,其中三个领域上提升超过1个BLEU,有效提高了神经机器翻译模型的翻译质量。''"
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<abstract>“k-最近邻机器翻译(kNN-MT)是近年来神经机器翻译领域的一个重要研究方向。此类方法可以在不更新机器翻译模型的情况下提高翻译质量,但训练数据中高低频单词的数量不均衡限制了模型效果,且固定的k值无法对处于不同密度分布的数据都产生良好的翻译结果。为此本文提出了一种创新的kNN-MT方法,引入确定性因子(CF)来降低数据不均衡对模型效果的影响,并根据测试点周边数据密度动态选择k值。在多领域德-英翻译数据集上,相比基线实验,本方法在四个领域上翻译效果均有提升,其中三个领域上提升超过1个BLEU,有效提高了神经机器翻译模型的翻译质量。”</abstract>
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%0 Conference Proceedings
%T 融合确定性因子及区域密度的k-最近邻机器翻译方法(A k-Nearest-Neighbor Machine Translation Method Combining Certainty Factor and Region Density)
%A Qi, Rui
%A Shi, Xiangyu
%A Man, Zhibo
%A Xu, Jinan
%A Chen, Yufeng
%Y Maosong, Sun
%Y Jiye, Liang
%Y Xianpei, Han
%Y Zhiyuan, Liu
%Y Yulan, He
%S Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)
%D 2024
%8 July
%I Chinese Information Processing Society of China
%C Taiyuan, China
%G zho
%F rui-etal-2024-rong
%X “k-最近邻机器翻译(kNN-MT)是近年来神经机器翻译领域的一个重要研究方向。此类方法可以在不更新机器翻译模型的情况下提高翻译质量,但训练数据中高低频单词的数量不均衡限制了模型效果,且固定的k值无法对处于不同密度分布的数据都产生良好的翻译结果。为此本文提出了一种创新的kNN-MT方法,引入确定性因子(CF)来降低数据不均衡对模型效果的影响,并根据测试点周边数据密度动态选择k值。在多领域德-英翻译数据集上,相比基线实验,本方法在四个领域上翻译效果均有提升,其中三个领域上提升超过1个BLEU,有效提高了神经机器翻译模型的翻译质量。”
%U https://aclanthology.org/2024.ccl-1.16/
%P 217-229
Markdown (Informal)
[融合确定性因子及区域密度的k-最近邻机器翻译方法(A k-Nearest-Neighbor Machine Translation Method Combining Certainty Factor and Region Density)](https://aclanthology.org/2024.ccl-1.16/) (Qi et al., CCL 2024)
ACL