no code implementations • WMT (EMNLP) 2020 • Shuangzhi Wu, Xing Wang, Longyue Wang, Fangxu Liu, Jun Xie, Zhaopeng Tu, Shuming Shi, Mu Li
This paper describes Tencent Neural Machine Translation systems for the WMT 2020 news translation tasks.
1 code implementation • Findings (NAACL) 2022 • Huan Lin, Baosong Yang, Liang Yao, Dayiheng Liu, Haibo Zhang, Jun Xie, Min Zhang, Jinsong Su
Diverse NMT aims at generating multiple diverse yet faithful translations given a source sentence.
1 code implementation • Findings (ACL) 2022 • Xingzhang Ren, Baosong Yang, Dayiheng Liu, Haibo Zhang, Xiaoyu Lv, Liang Yao, Jun Xie
Recognizing the language of ambiguous texts has become a main challenge in language identification (LID).
1 code implementation • 25 Nov 2022 • Pei Zhang, Baosong Yang, Haoran Wei, Dayiheng Liu, Kai Fan, Luo Si, Jun Xie
The lack of competency awareness makes NMT untrustworthy.
1 code implementation • 13 Nov 2022 • Binbin Xie, Xiangpeng Wei, Baosong Yang, Huan Lin, Jun Xie, Xiaoli Wang, Min Zhang, Jinsong Su
Keyphrase generation aims to automatically generate short phrases summarizing an input document.
no code implementations • 18 Oct 2022 • Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie
In this paper, we present our submission to the sentence-level MQM benchmark at Quality Estimation Shared Task, named UniTE (Unified Translation Evaluation).
no code implementations • 18 Oct 2022 • Yu Wan, Keqin Bao, Dayiheng Liu, Baosong Yang, Derek F. Wong, Lidia S. Chao, Wenqiang Lei, Jun Xie
In this report, we present our submission to the WMT 2022 Metrics Shared Task.
no code implementations • CVPR 2022 • Dahun Kim, Jun Xie, Huiyu Wang, Siyuan Qiao, Qihang Yu, Hong-Seok Kim, Hartwig Adam, In So Kweon, Liang-Chieh Chen
We present TubeFormer-DeepLab, the first attempt to tackle multiple core video segmentation tasks in a unified manner.
1 code implementation • 23 May 2022 • Yichao Du, Weizhi Wang, Zhirui Zhang, Boxing Chen, Tong Xu, Jun Xie, Enhong Chen
End-to-End Speech Translation (E2E-ST) has received increasing attention due to the potential of its less error propagation, lower latency, and fewer parameters.
no code implementations • 28 Apr 2022 • Kexin Yang, Dayiheng Liu, Wenqiang Lei, Baosong Yang, Mingfeng Xue, Boxing Chen, Jun Xie
We experimentally find that these prompts can be simply concatenated as a whole to multi-attribute CTG without any re-training, yet raises problems of fluency decrease and position sensitivity.
1 code implementation • ACL 2022 • Xiangpeng Wei, Heng Yu, Yue Hu, Rongxiang Weng, Weihua Luo, Jun Xie, Rong Jin
Although data augmentation is widely used to enrich the training data, conventional methods with discrete manipulations fail to generate diverse and faithful training samples.
no code implementations • Findings (ACL) 2022 • Fenfei Guo, Chen Zhang, Zhirui Zhang, Qixin He, Kejun Zhang, Jun Xie, Jordan Boyd-Graber
This paper develops automatic song translation (AST) for tonal languages and addresses the unique challenge of aligning words' tones with melody of a song in addition to conveying the original meaning.
no code implementations • 23 Mar 2022 • Jun Xie, Jiacheng Han, Dezhen Qi, Feng Chen, Kaer Huang, Jianwei Shuai
Recently, lane detection has made great progress in autonomous driving.
Ranked #2 on
Lane Detection
on TuSimple
1 code implementation • 27 Dec 2021 • Rui Wang, Jun Xie, Jiacheng Han, Dezhen Qi
Natural image matting is a fundamental and challenging computer vision task.
Ranked #5 on
Image Matting
on Composition-1K
1 code implementation • 21 Dec 2021 • Yichao Du, Zhirui Zhang, Weizhi Wang, Boxing Chen, Jun Xie, Tong Xu
In this paper, we attempt to model the joint probability of transcription and translation based on the speech input to directly leverage such triplet data.
2 code implementations • 28 Sep 2021 • Yiyi Liao, Jun Xie, Andreas Geiger
For the last few decades, several major subfields of artificial intelligence including computer vision, graphics, and robotics have progressed largely independently from each other.
1 code implementation • 23 Sep 2021 • Dongqi Wang, Haoran Wei, Zhirui Zhang, ShuJian Huang, Jun Xie, 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.
1 code implementation • Findings (EMNLP) 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.
1 code implementation • Findings (EMNLP) 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.
1 code implementation • 25 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.
1 code implementation • 17 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.
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.
1 code implementation • 23 Feb 2021 • Mark Weber, Jun Xie, Maxwell Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljoša Ošep, Laura Leal-Taixé, Liang-Chieh Chen
The task of assigning semantic classes and track identities to every pixel in a video is called video panoptic segmentation.
no code implementations • COLING 2020 • Deyu Zhou, Shuangzhi Wu, Qing Wang, Jun Xie, Zhaopeng Tu, Mu Li
Emotion lexicons have been shown effective for emotion classification (Baziotis et al., 2018).
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.
1 code implementation • ACL 2020 • Meihan Tong, Bin Xu, Shuai Wang, Yixin Cao, Lei Hou, Juanzi Li, Jun Xie
Event Detection (ED) is a fundamental task in automatically structuring texts.
1 code implementation • 19 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.
1 code implementation • 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.
1 code implementation • COLING 2020 • Sen yang, Leyang Cui, Jun Xie, Yue Zhang
In this paper, we conduct a study to exploit methods for better use of summary information.
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.
no code implementations • ACL 2019 • Bingzhen Wei, Mingxuan Wang, Hao Zhou, Junyang Lin, Jun Xie, Xu sun
Non-autoregressive translation models (NAT) have achieved impressive inference speedup.
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}.
no code implementations • WS 2018 • Mingxuan Wang, Li Gong, Wenhuan Zhu, Jun Xie, Chao Bian
We participated in the WMT 2018 shared news translation task on English↔Chinese language pair.
1 code implementation • EMNLP 2018 • Jiali Zeng, Jinsong Su, Huating Wen, Yang Liu, Jun Xie, Yongjing Yin, Jianqiang Zhao
Based on this intuition, in this paper, we devote to distinguishing and exploiting word-level domain contexts for multi-domain NMT.
1 code implementation • 27 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
no code implementations • COLING 2018 • Mingxuan Wang, Jun Xie, Zhixing Tan, Jinsong Su, Deyi Xiong, Chao Bian
Neural machine translation with source-side attention have achieved remarkable performance.
1 code implementation • 5 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.
Ranked #13 on
Semantic Role Labeling
on OntoNotes
no code implementations • CVPR 2016 • Jun Xie, Martin Kiefel, Ming-Ting Sun, Andreas Geiger
Semantic annotations are vital for training models for object recognition, semantic segmentation or scene understanding.
no code implementations • 28 Feb 2015 • Chongyang Zhang, Weiyao Lin, Wei Li, Bing Zhou, Jun Xie, Jijia Li
Image deblurring techniques play important roles in many image processing applications.
no code implementations • 21 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.