• #ACL2021NLP #ACL2021 Please check our group’s recent publication at the main conference of @aclmeeting. We uncovered a compositional generalization problem existing in NMT models and contributed a new dataset. Contributed by Yafu Li, Yongjing Yin, Yulong Chen, Yue Zhang.

  • Prof Yue Zhang leads the #NLP lab at Westlake University @Westlake_Uni. Our group focuses on machine learning-based natural language processing, as well as application-oriented tasks, such as web information extraction and financial market prediction. Welcome to join us!

  • #NLProc #ACL2021 G-Transformer for Document-level Machine Translation Paper:arxiv.org/abs/2105.14761 Code:github.com/baoguangsheng/ Our @aclmeeting paper at the main conference introduces locality bias to fix the failure of Transformer training on document-level MT data.

标签:ICCV

AAVAE: Augmentation-Augmented Variational Autoencoders

AAVAE: Augmentation-Augmented Variational Autoencoders William Falcon 1,2&Ananya Harsh Jha 1*&Teddy Koker 1&Kyunghyun Cho 2,31 Grid AI Labs2 New York University3 CIFAR……

H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction

H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction Eduard Ramon1,2   Gil Triginer1   Janna Escur1   Albert Pumarola3   Jaime Garcia1 &e……

Language Grounding with 3D Objects

Language Grounding with 3D Objects Jesse ThomasonUniversity of Southern California &Mohit Shridhar∗University of Washington/ANDYonatan BiskCarnegie Mellon University &……

CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows

CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localizationvia Conditional Normalizing Flows Denis Gudovskiy1    Shun Ishizaka2    ……

A Physiologically-adapted Gold Standard for Arousal During a Stress Induced Scenario

A Physiologically-adapted Gold Standard for ArousalDuring a Stress Induced Scenario Alice BairdChair EIHW, University of AugsburgAugsburg, Germany, Lukas StappenChair EIHW, ……

Contextual Transformer Networks for Visual Recognition

C++ontextual Transformer Networks for Visual Recognition Yehao Li, Ting Yao, Yingwei Pan, and Tao MeiJD AI Research, Beijing, China{yehaoli.sysu, tingyao.ustc, , Abstract Tran……

RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank

RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank Wenlong Zhang, Yihao Liu, Chao Dong, Yu QiaoWenlong Zhang, Yihao Liu, Chao Dong and Yu Qiao are w……

Anomaly Detection via Self-organizing Map

Anomaly Detection via Self-organizing Map Abstract Anomaly detection plays a key role in industrial manufacturing for product quality control. Traditional methods for anomaly dete……

ROMA: Free Lunch via Random Mappings for Unsupervised Visual Representation LearningTriplet is All You Need with Random Mappings for Unsupervised Visual Representation Learning

ROMA: Free Lunch via Random Mappings for Unsupervised Visual Representation Learning Wenbin Li1, Xuesong Yang1, Meihao Kong 1, Lei Wang2, Jing Huo1, Yang Gao1, Jiebo Luo31Nanjing ……

Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

Real-ESRGAN: Training Real-World Blind Super-Resolutionwith Pure Synthetic Data Xintao Wang1     Liangbin Xie∗2,3     Chao Dong2   ……