Mixup Decoding for Diverse Machine Translation

Mixup Decoding for Diverse Machine Translation

8 September 2021

Papers citing "Mixup Decoding for Diverse Machine Translation"

10 / 10 papers shown

Title
EDT: Improving Large Language Models' Generation by Entropy-based Dynamic Temperature Sampling Shimao Zhang Yu Bao Shujian Huang 20 8 0 21 Mar 2024
Generating Diverse Translation with Perturbed kNN-MT Yuto Nishida Makoto Morishita Hidetaka Kamigaito Taro Watanabe 11 1 0 14 Feb 2024
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation Muthuraman Chidambaram Rong Ge AAML 18 0 0 10 Feb 2024
To Diverge or Not to Diverge: A Morphosyntactic Perspective on Machine Translation vs Human Translation Jiaming Luo Colin Cherry George F. Foster 15 4 0 02 Jan 2024
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability Chengtai Cao Fan Zhou Yurou Dai Jianping Wang Kunpeng Zhang AAML 16 27 0 21 Dec 2022
Exploring Diversity in Back Translation for Low-Resource Machine Translation Laurie Burchell Alexandra Birch Kenneth Heafield 24 15 0 01 Jun 2022
One Reference Is Not Enough: Diverse Distillation with Reference Selection for Non-Autoregressive Translation Chenze Shao Xuanfu Wu Yang Feng 15 22 0 28 May 2022
STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation Qingkai Fang Rong Ye Lei Li Yang Feng Mingxuan Wang 22 95 0 20 Mar 2022
Neural Machine Translation with Phrase-Level Universal Visual Representations Qingkai Fang Yang Feng 26 40 0 19 Mar 2022
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,724 0 26 Sep 2016