Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Jie Zhou

Jie Zhou

Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings


Oct 13, 2021
Shaopeng Lai, Ante Wang, Fandong Meng, Jie Zhou, Yubin Ge, Jiali Zeng, Junfeng Yao, Degen Huang, Jinsong Su

Figure 1 for Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings
Figure 2 for Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings
Figure 3 for Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings
Figure 4 for Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings
* EMNLP 2021 
  Access Paper or Ask Questions

WeTS: A Benchmark for Translation Suggestion


Oct 11, 2021
Zhen Yang, Yingxue Zhang, Ernan Li, Fandong Meng, Jie Zhou

Figure 1 for WeTS: A Benchmark for Translation Suggestion
Figure 2 for WeTS: A Benchmark for Translation Suggestion
Figure 3 for WeTS: A Benchmark for Translation Suggestion
Figure 4 for WeTS: A Benchmark for Translation Suggestion
* Translation suggestion, Transformer 
  Access Paper or Ask Questions

Topology-Imbalance Learning for Semi-Supervised Node Classification


Oct 08, 2021
Deli Chen, Yankai Lin, Guangxiang Zhao, Xuancheng Ren, Peng Li, Jie Zhou, Xu Sun

Figure 1 for Topology-Imbalance Learning for Semi-Supervised Node Classification
Figure 2 for Topology-Imbalance Learning for Semi-Supervised Node Classification
Figure 3 for Topology-Imbalance Learning for Semi-Supervised Node Classification
Figure 4 for Topology-Imbalance Learning for Semi-Supervised Node Classification
* Accepted By NeurIPS 2021 
  Access Paper or Ask Questions

MoEfication: Conditional Computation of Transformer Models for Efficient Inference


Oct 05, 2021
Zhengyan Zhang, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou

Figure 1 for MoEfication: Conditional Computation of Transformer Models for Efficient Inference
Figure 2 for MoEfication: Conditional Computation of Transformer Models for Efficient Inference
Figure 3 for MoEfication: Conditional Computation of Transformer Models for Efficient Inference
Figure 4 for MoEfication: Conditional Computation of Transformer Models for Efficient Inference
* Work in progress 
  Access Paper or Ask Questions

Simulated annealing for optimization of graphs and sequences


Oct 01, 2021
Xianggen Liu, Pengyong Li, Fandong Meng, Hao Zhou, Huasong Zhong, Jie Zhou, Lili Mou, Sen Song

Figure 1 for Simulated annealing for optimization of graphs and sequences
Figure 2 for Simulated annealing for optimization of graphs and sequences
Figure 3 for Simulated annealing for optimization of graphs and sequences
Figure 4 for Simulated annealing for optimization of graphs and sequences
* Neurocomputing, 465:310-324 (2021) 
 * This article is an accepted manuscript of Neurocomputing. arXiv admin note: substantial text overlap with arXiv:1909.03588 
  Access Paper or Ask Questions

Structure-Preserving Image Super-Resolution


Sep 26, 2021
Cheng Ma, Yongming Rao, Jiwen Lu, Jie Zhou

Figure 1 for Structure-Preserving Image Super-Resolution
Figure 2 for Structure-Preserving Image Super-Resolution
Figure 3 for Structure-Preserving Image Super-Resolution
Figure 4 for Structure-Preserving Image Super-Resolution
* Accepted by T-PAMI. Journal version of arXiv:2003.13081 (CVPR 2020) 
  Access Paper or Ask Questions

Dynamic Knowledge Distillation for Pre-trained Language Models


Sep 23, 2021
Lei Li, Yankai Lin, Shuhuai Ren, Peng Li, Jie Zhou, Xu Sun

Figure 1 for Dynamic Knowledge Distillation for Pre-trained Language Models
Figure 2 for Dynamic Knowledge Distillation for Pre-trained Language Models
Figure 3 for Dynamic Knowledge Distillation for Pre-trained Language Models
Figure 4 for Dynamic Knowledge Distillation for Pre-trained Language Models
* Main Conference EMNLP 2021, Camera Ready 
  Access Paper or Ask Questions

Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation


Sep 18, 2021
Lei Shen, Jinchao Zhang, Jiao Ou, Xiaofang Zhao, Jie Zhou

Figure 1 for Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation
Figure 2 for Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation
Figure 3 for Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation
Figure 4 for Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation
* Accepted by EMNLP 2021 Findings 
  Access Paper or Ask Questions

Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation


Sep 17, 2021
Feilong Chen, Fandong Meng, Xiuyi Chen, Peng Li, Jie Zhou

Figure 1 for Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation
Figure 2 for Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation
Figure 3 for Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation
Figure 4 for Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation
* ACL Fingdings 2021 
  Access Paper or Ask Questions

GoG: Relation-aware Graph-over-Graph Network for Visual Dialog


Sep 17, 2021
Feilong Chen, Xiuyi Chen, Fandong Meng, Peng Li, Jie Zhou

Figure 1 for GoG: Relation-aware Graph-over-Graph Network for Visual Dialog
Figure 2 for GoG: Relation-aware Graph-over-Graph Network for Visual Dialog
Figure 3 for GoG: Relation-aware Graph-over-Graph Network for Visual Dialog
Figure 4 for GoG: Relation-aware Graph-over-Graph Network for Visual Dialog
* ACL Findings 2021. arXiv admin note: text overlap with arXiv:2109.06013 
  Access Paper or Ask Questions

Challenging Instances are Worth Learning: Generating Valuable Negative Samples for Response Selection Training


Sep 14, 2021
Yao Qiu, Jinchao Zhang, Huiying Ren, Jie Zhou

Figure 1 for Challenging Instances are Worth Learning: Generating Valuable Negative Samples for Response Selection Training
Figure 2 for Challenging Instances are Worth Learning: Generating Valuable Negative Samples for Response Selection Training
Figure 3 for Challenging Instances are Worth Learning: Generating Valuable Negative Samples for Response Selection Training
Figure 4 for Challenging Instances are Worth Learning: Generating Valuable Negative Samples for Response Selection Training

  Access Paper or Ask Questions

Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder


Sep 14, 2021
Yao Qiu, Jinchao Zhang, Jie Zhou

Figure 1 for Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder
Figure 2 for Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder
Figure 3 for Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder
Figure 4 for Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder
* Accepted as a long paper at ACL 2021 (Findings) 
  Access Paper or Ask Questions

Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks


Sep 14, 2021
Yao Qiu, Jinchao Zhang, Jie Zhou

Figure 1 for Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks
Figure 2 for Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks
Figure 3 for Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks
Figure 4 for Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks
* Accepted as a long paper at EMNLP 2021 (Main Conference) 
  Access Paper or Ask Questions

Structure-Enhanced Pop Music Generation via Harmony-Aware Learning


Sep 14, 2021
Xueyao Zhang, Jinchao Zhang, Yao Qiu, Li Wang, Jie Zhou

Figure 1 for Structure-Enhanced Pop Music Generation via Harmony-Aware Learning
Figure 2 for Structure-Enhanced Pop Music Generation via Harmony-Aware Learning
Figure 3 for Structure-Enhanced Pop Music Generation via Harmony-Aware Learning
Figure 4 for Structure-Enhanced Pop Music Generation via Harmony-Aware Learning
* Under review 
  Access Paper or Ask Questions

Competence-based Curriculum Learning for Multilingual Machine Translation


Sep 09, 2021
Mingliang Zhang, Fandong Meng, Yunhai Tong, Jie Zhou

Figure 1 for Competence-based Curriculum Learning for Multilingual Machine Translation
Figure 2 for Competence-based Curriculum Learning for Multilingual Machine Translation
Figure 3 for Competence-based Curriculum Learning for Multilingual Machine Translation
Figure 4 for Competence-based Curriculum Learning for Multilingual Machine Translation
* Accepted by Findings of EMNLP 2021. We release the codes at https://github.com/zml24/ccl-m 
  Access Paper or Ask Questions

Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented Guesser


Sep 06, 2021
Duo Zheng, Zipeng Xu, Fandong Meng, Xiaojie Wang, Jiaan Wang, Jie Zhou

Figure 1 for Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented Guesser
Figure 2 for Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented Guesser
Figure 3 for Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented Guesser
Figure 4 for Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented Guesser
* Accepted by Findings of EMNLP 2021. Code is available at: https://github.com/zd11024/Entity_Questioner 
  Access Paper or Ask Questions

Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical


Sep 06, 2021
Wanhua Li, Jiwen Lu, Abudukelimu Wuerkaixi, Jianjiang Feng, Jie Zhou

Figure 1 for Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical
Figure 2 for Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical
Figure 3 for Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical
Figure 4 for Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical
* IEEE Transactions on Image Processing, vol. 30, pp. 4947-4961, 2021 
 * Accepted by IEEE Transactions on Image Processing (TIP) 
  Access Paper or Ask Questions

Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark


Sep 04, 2021
Zhengcong Fei, Zekang Li, Jinchao Zhang, Yang Feng, Jie Zhou

Figure 1 for Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark
Figure 2 for Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark
Figure 3 for Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark
Figure 4 for Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark

  Access Paper or Ask Questions

NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo


Sep 03, 2021
Yi Wei, Shaohui Liu, Yongming Rao, Wang Zhao, Jiwen Lu, Jie Zhou

Figure 1 for NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
Figure 2 for NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
Figure 3 for NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
Figure 4 for NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
* To appear in ICCV 2021 (Oral). Project page: https://weiyithu.github.io/NerfingMVS/ 
  Access Paper or Ask Questions

Towards Making the Most of Dialogue Characteristics for Neural Chat Translation


Sep 02, 2021
Yunlong Liang, Chulun Zhou, Fandong Meng, Jinan Xu, Yufeng Chen, Jinsong Su, Jie Zhou

Figure 1 for Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
Figure 2 for Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
Figure 3 for Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
Figure 4 for Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
* Accepted as a long paper at EMNLP 2021 main conference. The first two authors contributed equally. Code: https://github.com/XL2248/CSA-NCT 
  Access Paper or Ask Questions

Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification


Sep 01, 2021
Shuhuai Ren, Jinchao Zhang, Lei Li, Xu Sun, Jie Zhou

Figure 1 for Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification
Figure 2 for Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification
Figure 3 for Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification
Figure 4 for Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification
* Accepted by EMNLP 2021 main conference (Long Paper) 
  Access Paper or Ask Questions

Scheduled Sampling Based on Decoding Steps for Neural Machine Translation


Aug 31, 2021
Yijin Liu, Fandong Meng, Yufeng Chen, Jinan Xu, Jie Zhou

Figure 1 for Scheduled Sampling Based on Decoding Steps for Neural Machine Translation
Figure 2 for Scheduled Sampling Based on Decoding Steps for Neural Machine Translation
Figure 3 for Scheduled Sampling Based on Decoding Steps for Neural Machine Translation
Figure 4 for Scheduled Sampling Based on Decoding Steps for Neural Machine Translation
* Code is at https://github.com/Adaxry/ss_on_decoding_steps. To appear in EMNLP-2021 main conference. arXiv admin note: text overlap with arXiv:2107.10427 
  Access Paper or Ask Questions

Deep Relational Metric Learning


Aug 23, 2021
Wenzhao Zheng, Borui Zhang, Jiwen Lu, Jie Zhou

Figure 1 for Deep Relational Metric Learning
Figure 2 for Deep Relational Metric Learning
Figure 3 for Deep Relational Metric Learning
Figure 4 for Deep Relational Metric Learning
* Accepted to ICCV 2021. Source code available at https://github.com/zbr17/DRML 
  Access Paper or Ask Questions

PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers


Aug 19, 2021
Xumin Yu, Yongming Rao, Ziyi Wang, Zuyan Liu, Jiwen Lu, Jie Zhou

Figure 1 for PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
Figure 2 for PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
Figure 3 for PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
Figure 4 for PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
* Accepted to ICCV 2021 (Oral Presentation) 
  Access Paper or Ask Questions

Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification


Aug 19, 2021
Yongming Rao, Guangyi Chen, Jiwen Lu, Jie Zhou

Figure 1 for Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Figure 2 for Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Figure 3 for Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Figure 4 for Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
* Accepted to ICCV 2021 
  Access Paper or Ask Questions

Group-aware Contrastive Regression for Action Quality Assessment


Aug 17, 2021
Xumin Yu, Yongming Rao, Wenliang Zhao, Jiwen Lu, Jie Zhou

Figure 1 for Group-aware Contrastive Regression for Action Quality Assessment
Figure 2 for Group-aware Contrastive Regression for Action Quality Assessment
Figure 3 for Group-aware Contrastive Regression for Action Quality Assessment
Figure 4 for Group-aware Contrastive Regression for Action Quality Assessment
* Accepted to ICCV 2021 
  Access Paper or Ask Questions

RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection


Aug 17, 2021
Yongming Rao, Benlin Liu, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, Jie Zhou

Figure 1 for RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection
Figure 2 for RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection
Figure 3 for RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection
Figure 4 for RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection
* Accepted to ICCV 2021 
  Access Paper or Ask Questions

Masked Face Recognition Challenge: The WebFace260M Track Report


Aug 16, 2021
Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, Junjie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Jia Guo, Jiwen Lu, Dalong Du, Jie Zhou

Figure 1 for Masked Face Recognition Challenge: The WebFace260M Track Report
Figure 2 for Masked Face Recognition Challenge: The WebFace260M Track Report
Figure 3 for Masked Face Recognition Challenge: The WebFace260M Track Report
Figure 4 for Masked Face Recognition Challenge: The WebFace260M Track Report
* The WebFace260M Track of ICCV-21 MFR Challenge is still open in https://www.face-benchmark.org/challenge.html 
  Access Paper or Ask Questions

Towards Interpretable Deep Metric Learning with Structural Matching


Aug 12, 2021
Wenliang Zhao, Yongming Rao, Ziyi Wang, Jiwen Lu, Jie Zhou

Figure 1 for Towards Interpretable Deep Metric Learning with Structural Matching
Figure 2 for Towards Interpretable Deep Metric Learning with Structural Matching
Figure 3 for Towards Interpretable Deep Metric Learning with Structural Matching
Figure 4 for Towards Interpretable Deep Metric Learning with Structural Matching
* Accepted to ICCV 2021 
  Access Paper or Ask Questions

PatrickStar: Parallel Training of Pre-trained Models via a Chunk-based Memory Management


Aug 12, 2021
Jiarui Fang, Yang Yu, Shenggui Li, Yang You, Jie Zhou

Figure 1 for PatrickStar: Parallel Training of Pre-trained Models via a Chunk-based Memory Management
Figure 2 for PatrickStar: Parallel Training of Pre-trained Models via a Chunk-based Memory Management
Figure 3 for PatrickStar: Parallel Training of Pre-trained Models via a Chunk-based Memory Management
Figure 4 for PatrickStar: Parallel Training of Pre-trained Models via a Chunk-based Memory Management
* 11 pages 
  Access Paper or Ask Questions