Zhaopeng Tu

Target Foresight Based Attention for Neural Machine Translation

2018

Xintong Li, Lemao Liu, Zhaopeng Tu, Shuming Shi, Max Meng. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). 2018.

Information Aggregation for Multi-Head Attention with Routing-by-Agreement

2019

Jian Li, Baosong Yang, Zi-Yi Dou, Xing Wang, Michael R. Lyu, Zhaopeng Tu. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long …

TranSmart: A Practical Interactive Machine Translation System

2021 · arXiv (Cornell University)

Automatic machine translation is super efficient to produce translations yet their quality is not guaranteed. This technique report introduces TranSmart, a practical human-machine interactive translation system that is able to trade off translation quality and …

A Template-based Method for Constrained Neural Machine Translation

2022 · arXiv (Cornell University)

Machine translation systems are expected to cope with various types of constraints in many practical scenarios. While neural machine translation (NMT) has achieved strong performance in unconstrained cases, it is non-trivial to impose pre-specified constraints …

Scaling Back-Translation with Domain Text Generation for Sign Language Gloss Translation

2023

Sign language gloss translation aims to translate the sign glosses into spoken language texts, which is challenging due to the scarcity of labeled gloss-text parallel data. Back-translation (BT), which generates pseudo parallel data by translating …

Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model

2024

Zhiwei He, Xing Wang, Wenxiang Jiao, Zhuosheng Zhang, Rui Wang, Shuming Shi, Zhaopeng Tu. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: …

Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation

2024

Longyue Wang, Siyou Liu, Chenyang Lyu, Wenxiang Jiao, Xing Wang, Jiahao Xu, Zhaopeng Tu, Yan Gu, Weiyu Chen, Minghao Wu, Liting Zhou, Philipp Koehn, Andy Way, Yulin Yuan. Proceedings of the Ninth Conference on Machine …

Modeling Coverage for Neural Machine Translation

2016 · arXiv (Cornell University)

Attention mechanism has enhanced state-of-the-art Neural Machine Translation (NMT) by jointly learning to align and translate. It tends to ignore past alignment information, however, which often leads to over-translation and under-translation. To address this problem, …

Multi-Head Attention with Disagreement Regularization

2018

Multi-head attention is appealing for the ability to jointly attend to information from different representation subspaces at different positions. In this work, we introduce a disagreement regularization to explicitly encourage the diversity among multiple attention …

Learning to Remember Translation History with a Continuous Cache

2018 · Transactions of the Association for Computational Linguistics

Existing neural machine translation (NMT) models generally translate sentences in isolation, missing the opportunity to take advantage of document-level information. In this work, we propose to augment NMT models with a very light-weight cache-like memory …

Modeling Source Syntax for Neural Machine Translation

2017

Even though a linguistics-free sequence to sequence model in neural machine translation (NMT) has certain capability of implicitly learning syntactic information of source sentences, this paper shows that source syntax can be explicitly incorporated into …

Modeling Localness for Self-Attention Networks

2018

Self-attention networks have proven to be of profound value for its strength of capturing global dependencies. In this work, we propose to model localness for self-attention networks, which enhances the ability of capturing useful local …