Search Results for author: Jun Xie

Found 31 papers, 11 papers with code

Non-Parametric Online Learning from Human Feedback for Neural Machine Translation

no code implementations23 Sep 2021 Dongqi Wang, Haoran Wei, Zhirui Zhang, ShuJian Huang, Jun Xie, Weihua Luo, Jiajun Chen

We study the problem of online learning with human feedback in the human-in-the-loop machine translation, in which the human translators revise the machine-generated translations and then the corrected translations are used to improve the neural machine translation (NMT) system.

Machine Translation

Non-Parametric Unsupervised Domain Adaptation for Neural Machine Translation

1 code implementation14 Sep 2021 Xin Zheng, Zhirui Zhang, ShuJian Huang, Boxing Chen, Jun Xie, Weihua Luo, Jiajun Chen

Recently, $k$NN-MT has shown the promising capability of directly incorporating the pre-trained neural machine translation (NMT) model with domain-specific token-level $k$-nearest-neighbor ($k$NN) retrieval to achieve domain adaptation without retraining.

Machine Translation Unsupervised Domain Adaptation

Rethinking Zero-shot Neural Machine Translation: From a Perspective of Latent Variables

1 code implementation10 Sep 2021 Weizhi Wang, Zhirui Zhang, Yichao Du, Boxing Chen, Jun Xie, Weihua Luo

However, it usually suffers from capturing spurious correlations between the output language and language invariant semantics due to the maximum likelihood training objective, leading to poor transfer performance on zero-shot translation.

Denoising Machine Translation

Product-oriented Machine Translation with Cross-modal Cross-lingual Pre-training

1 code implementation25 Aug 2021 Yuqing Song, ShiZhe Chen, Qin Jin, Wei Luo, Jun Xie, Fei Huang

Firstly, there are many specialized jargons in the product description, which are ambiguous to translate without the product image.

Machine Translation

DeepLab2: A TensorFlow Library for Deep Labeling

1 code implementation17 Jun 2021 Mark Weber, Huiyu Wang, Siyuan Qiao, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixe, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen

DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a state-of-the-art and easy-to-use TensorFlow codebase for general dense pixel prediction problems in computer vision.

Context-Interactive Pre-Training for Document Machine Translation

no code implementations NAACL 2021 Pengcheng Yang, Pei Zhang, Boxing Chen, Jun Xie, Weihua Luo

Document machine translation aims to translate the source sentence into the target language in the presence of additional contextual information.

Machine Translation

STEP: Segmenting and Tracking Every Pixel

no code implementations23 Feb 2021 Mark Weber, Jun Xie, Maxwell Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljosa Osep, Laura Leal-Taixe, Liang-Chieh Chen

Our work is the first that targets this task in a real-world setting that requires dense interpretation in both spatial and temporal domains.

Panoptic Segmentation

What Have We Achieved on Text Summarization?

1 code implementation EMNLP 2020 Dandan Huang, Leyang Cui, Sen yang, Guangsheng Bao, Kun Wang, Jun Xie, Yue Zhang

Deep learning has led to significant improvement in text summarization with various methods investigated and improved ROUGE scores reported over the years.

Text Summarization

Neural Simile Recognition with Cyclic Multitask Learning and Local Attention

1 code implementation19 Dec 2019 Jiali Zeng, Linfeng Song, Jinsong Su, Jun Xie, Wei Song, Jiebo Luo

Simile recognition is to detect simile sentences and to extract simile components, i. e., tenors and vehicles.

Sentence Classification

A Reinforced Generation of Adversarial Examples for Neural Machine Translation

no code implementations ACL 2020 Wei Zou, Shu-Jian Huang, Jun Xie, Xin-yu Dai, Jia-Jun Chen

Neural machine translation systems tend to fail on less decent inputs despite its significant efficacy, which may significantly harm the credibility of this systems-fathoming how and when neural-based systems fail in such cases is critical for industrial maintenance.

Machine Translation

Specificity-Driven Cascading Approach for Unsupervised Sentiment Modification

no code implementations IJCNLP 2019 Pengcheng Yang, Junyang Lin, Jingjing Xu, Jun Xie, Qi Su, Xu sun

The task of unsupervised sentiment modification aims to reverse the sentiment polarity of the input text while preserving its semantic content without any parallel data.

Towards Linear Time Neural Machine Translation with Capsule Networks

no code implementations IJCNLP 2019 Mingxuan Wang, Jun Xie, Zhixing Tan, Jinsong Su, Deyi Xiong, Lei LI

In this study, we first investigate a novel capsule network with dynamic routing for linear time Neural Machine Translation (NMT), referred as \textsc{CapsNMT}.

Machine Translation

Cauchy combination test: a powerful test with analytic p-value calculation under arbitrary dependency structures

1 code implementation27 Aug 2018 Yaowu Liu, Jun Xie

We prove a non-asymptotic result that the tail of the null distribution of our proposed test statistic can be well approximated by a Cauchy distribution under arbitrary dependency structures.

Methodology Statistics Theory Statistics Theory

Deep Semantic Role Labeling with Self-Attention

1 code implementation5 Dec 2017 Zhixing Tan, Mingxuan Wang, Jun Xie, Yidong Chen, Xiaodong Shi

Semantic Role Labeling (SRL) is believed to be a crucial step towards natural language understanding and has been widely studied.

Natural Language Understanding Semantic Role Labeling

Intra-and-Inter-Constraint-based Video Enhancement based on Piecewise Tone Mapping

no code implementations21 Feb 2015 Yuanzhe Chen, Weiyao Lin, Chongyang Zhang, Zhenzhong Chen, Ning Xu, Jun Xie

In this paper, we propose a new intra-and-inter-constraint-based video enhancement approach aiming to 1) achieve high intra-frame quality of the entire picture where multiple region-of-interests (ROIs) can be adaptively and simultaneously enhanced, and 2) guarantee the inter-frame quality consistencies among video frames.

Tone Mapping Video Enhancement

Cannot find the paper you are looking for? You can Submit a new open access paper.