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 Yong Li

Yong Li

M6: A Chinese Multimodal Pretrainer


Mar 02, 2021
Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang

Figure 1 for M6: A Chinese Multimodal Pretrainer
Figure 2 for M6: A Chinese Multimodal Pretrainer
Figure 3 for M6: A Chinese Multimodal Pretrainer
Figure 4 for M6: A Chinese Multimodal Pretrainer
* 12 pages, technical report 
  Access Paper or Ask Questions

Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network


Feb 21, 2021
Zhenyu Han, Fengli Xu, Jinghan Shi, Yu Shang, Haorui Ma, Pan Hui, Yong Li

Figure 1 for Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network
Figure 2 for Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network
Figure 3 for Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network
Figure 4 for Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network
* Published in Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM '20) 
  Access Paper or Ask Questions

Reinforced Contact Tracing and Epidemic Intervention


Feb 04, 2021
Tao Feng, Sirui Song, Tong Xia, Yong Li

Figure 1 for Reinforced Contact Tracing and Epidemic Intervention
Figure 2 for Reinforced Contact Tracing and Epidemic Intervention
Figure 3 for Reinforced Contact Tracing and Epidemic Intervention
Figure 4 for Reinforced Contact Tracing and Epidemic Intervention

  Access Paper or Ask Questions

Learnable Embedding Sizes for Recommender Systems


Jan 19, 2021
Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, Yong Li

Figure 1 for Learnable Embedding Sizes for Recommender Systems
Figure 2 for Learnable Embedding Sizes for Recommender Systems
Figure 3 for Learnable Embedding Sizes for Recommender Systems
Figure 4 for Learnable Embedding Sizes for Recommender Systems
* International Conference on Learning Representations (ICLR), 2021 
  Access Paper or Ask Questions

AttnMove: History Enhanced Trajectory Recovery via Attentional Network


Jan 03, 2021
Tong Xia, Yunhan Qi, Jie Feng, Fengli Xu, Funing Sun, Diansheng Guo, Yong Li

Figure 1 for AttnMove: History Enhanced Trajectory Recovery via Attentional Network
Figure 2 for AttnMove: History Enhanced Trajectory Recovery via Attentional Network
Figure 3 for AttnMove: History Enhanced Trajectory Recovery via Attentional Network
Figure 4 for AttnMove: History Enhanced Trajectory Recovery via Attentional Network

  Access Paper or Ask Questions

Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training


Dec 16, 2020
Chen Xing, Wencong Xiao, Yong Li, Wei Lin

Figure 1 for Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training
Figure 2 for Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training
Figure 3 for Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training
Figure 4 for Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training

  Access Paper or Ask Questions

EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications


Nov 23, 2020
Minghui Qiu, Peng Li, Hanjie Pan, Chengyu Wang, Ang Wang, Cen Chen, Yaliang Li, Dehong Gao, Jun Huang, Yong Li, Jun Yang, Deng Cai, Wei Lin

Figure 1 for EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications
Figure 2 for EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications
Figure 3 for EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications
* 4 pages 
  Access Paper or Ask Questions

Probability-Density-Based Deep Learning Paradigm for the Fuzzy Design of Functional Metastructures


Nov 11, 2020
Ying-Tao Luo, Peng-Qi Li, Dong-Ting Li, Yu-Gui Peng, Zhi-Guo Geng, Shu-Huan Xie, Yong Li, Andrea Alu, Jie Zhu, Xue-Feng Zhu

* Research, vol. 2020, Article ID 8757403, 2020 
 * Published in Research, an AAAS Science Partner Journal 
  Access Paper or Ask Questions

Graph Neural Network with Automorphic Equivalence Filters


Nov 09, 2020
Fengli Xu, Quanming Yao, Pan Hui, Yong Li

Figure 1 for Graph Neural Network with Automorphic Equivalence Filters
Figure 2 for Graph Neural Network with Automorphic Equivalence Filters
Figure 3 for Graph Neural Network with Automorphic Equivalence Filters
Figure 4 for Graph Neural Network with Automorphic Equivalence Filters

  Access Paper or Ask Questions

VEGA: Towards an End-to-End Configurable AutoML Pipeline


Nov 05, 2020
Bochao Wang, Hang Xu, Jiajin Zhang, Chen Chen, Xiaozhi Fang, Ning Kang, Lanqing Hong, Wei Zhang, Yong Li, Zhicheng Liu, Zhenguo Li, Wenzhi Liu, Tong Zhang

Figure 1 for VEGA: Towards an End-to-End Configurable AutoML Pipeline
Figure 2 for VEGA: Towards an End-to-End Configurable AutoML Pipeline
Figure 3 for VEGA: Towards an End-to-End Configurable AutoML Pipeline
Figure 4 for VEGA: Towards an End-to-End Configurable AutoML Pipeline
* AutoML pipeline. Code is open-sourced at https://github.com/huawei-noah/vega 
  Access Paper or Ask Questions

MicroRec: Accelerating Deep Recommendation Systems to Microseconds by Hardware and Data Structure Solutions


Oct 12, 2020
Wenqi Jiang, Zhenhao He, Shuai Zhang, Thomas B. Preußer, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso

* Under submission 
  Access Paper or Ask Questions

Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering


Sep 07, 2020
Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, Depeng Jin

Figure 1 for Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
Figure 2 for Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
Figure 3 for Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
Figure 4 for Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
* 20 pages, 7 figures, 8 tables 
  Access Paper or Ask Questions

Reinforced Epidemic Control: Saving Both Lives and Economy


Aug 04, 2020
Sirui Song, Zefang Zong, Yong Li, Xue Liu, Yang Yu

Figure 1 for Reinforced Epidemic Control: Saving Both Lives and Economy
Figure 2 for Reinforced Epidemic Control: Saving Both Lives and Economy
Figure 3 for Reinforced Epidemic Control: Saving Both Lives and Economy
Figure 4 for Reinforced Epidemic Control: Saving Both Lives and Economy
* Accepted by KDD'20 "AI For Covid-19" Initiative 
  Access Paper or Ask Questions

DeepNetQoE: Self-adaptive QoE Optimization Framework of Deep Networks


Jul 17, 2020
Rui Wang, Min Chen, Nadra Guizani, Yong Li, Hamid Gharavi, Kai Hwang

Figure 1 for DeepNetQoE: Self-adaptive QoE Optimization Framework of Deep Networks
Figure 2 for DeepNetQoE: Self-adaptive QoE Optimization Framework of Deep Networks
Figure 3 for DeepNetQoE: Self-adaptive QoE Optimization Framework of Deep Networks
Figure 4 for DeepNetQoE: Self-adaptive QoE Optimization Framework of Deep Networks

  Access Paper or Ask Questions

Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases


Jul 08, 2020
Yu Liu, Quanming Yao, Yong Li

Figure 1 for Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases
Figure 2 for Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases
Figure 3 for Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases
Figure 4 for Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases
* WWW 2020 
  Access Paper or Ask Questions

Proving Non-Inclusion of Büchi Automata based on Monte Carlo Sampling


Jul 07, 2020
Yong Li, Andrea Turrini, Xuechao Sun, Lijun Zhang

Figure 1 for Proving Non-Inclusion of Büchi Automata based on Monte Carlo Sampling
Figure 2 for Proving Non-Inclusion of Büchi Automata based on Monte Carlo Sampling
Figure 3 for Proving Non-Inclusion of Büchi Automata based on Monte Carlo Sampling
Figure 4 for Proving Non-Inclusion of Büchi Automata based on Monte Carlo Sampling
* Accepted to ATVA 2020; typos corrected; authors corrected 
  Access Paper or Ask Questions

On the Power of Unambiguity in Büchi Complementation


May 18, 2020
Yong Li, Moshe Y. Vardi, Lijun Zhang

Figure 1 for On the Power of Unambiguity in Büchi Complementation
Figure 2 for On the Power of Unambiguity in Büchi Complementation

  Access Paper or Ask Questions

Bundle Recommendation with Graph Convolutional Networks


May 07, 2020
Jianxin Chang, Chen Gao, Xiangnan He, Yong Li, Depeng Jin

Figure 1 for Bundle Recommendation with Graph Convolutional Networks
Figure 2 for Bundle Recommendation with Graph Convolutional Networks
Figure 3 for Bundle Recommendation with Graph Convolutional Networks
Figure 4 for Bundle Recommendation with Graph Convolutional Networks
* Accepted by SIGIR 2020 (Short) 
  Access Paper or Ask Questions

Urban Anomaly Analytics: Description, Detection, and Prediction


Apr 25, 2020
Mingyang Zhang, Tong Li, Yue Yu, Yong Li, Pan Hui, Yu Zheng

Figure 1 for Urban Anomaly Analytics: Description, Detection, and Prediction
Figure 2 for Urban Anomaly Analytics: Description, Detection, and Prediction
Figure 3 for Urban Anomaly Analytics: Description, Detection, and Prediction
Figure 4 for Urban Anomaly Analytics: Description, Detection, and Prediction
* Accepted by IEEE Transactions on Big Data 
  Access Paper or Ask Questions

A Survey on Edge Intelligence


Mar 26, 2020
Dianlei Xu, Tong Li, Yong Li, Xiang Su, Sasu Tarkoma, Pan Hui

Figure 1 for A Survey on Edge Intelligence
Figure 2 for A Survey on Edge Intelligence
Figure 3 for A Survey on Edge Intelligence
Figure 4 for A Survey on Edge Intelligence

  Access Paper or Ask Questions

Hybrid Compositional Reasoning for Reactive Synthesis from Finite-Horizon Specifications


Dec 09, 2019
Suguman Bansal, Yong Li, Lucas M. Tabajara, Moshe Y. Vardi

Figure 1 for Hybrid Compositional Reasoning for Reactive Synthesis from Finite-Horizon Specifications
Figure 2 for Hybrid Compositional Reasoning for Reactive Synthesis from Finite-Horizon Specifications
Figure 3 for Hybrid Compositional Reasoning for Reactive Synthesis from Finite-Horizon Specifications
Figure 4 for Hybrid Compositional Reasoning for Reactive Synthesis from Finite-Horizon Specifications
* Accepted by AAAI 2020 
  Access Paper or Ask Questions

Adaptive Context Network for Scene Parsing


Nov 05, 2019
Jun Fu, Jing Liu, Yuhang Wang, Yong Li, Yongjun Bao, Jinhui Tang, Hanqing Lu

Figure 1 for Adaptive Context Network for Scene Parsing
Figure 2 for Adaptive Context Network for Scene Parsing
Figure 3 for Adaptive Context Network for Scene Parsing
Figure 4 for Adaptive Context Network for Scene Parsing
* International Conference on Computer Vision 2019 
 * Accepted by ICCV 2019 
  Access Paper or Ask Questions

UrbanRhythm: Revealing Urban Dynamics Hidden in Mobility Data


Nov 03, 2019
Sirui Song, Tong Xia, Depeng Jin, Pan Hui, Yong Li

Figure 1 for UrbanRhythm: Revealing Urban Dynamics Hidden in Mobility Data
Figure 2 for UrbanRhythm: Revealing Urban Dynamics Hidden in Mobility Data
Figure 3 for UrbanRhythm: Revealing Urban Dynamics Hidden in Mobility Data
Figure 4 for UrbanRhythm: Revealing Urban Dynamics Hidden in Mobility Data
* Submitted to IEEE Transactions on Knowledge and Data Engineering (TKDE) 
  Access Paper or Ask Questions

Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection


Sep 18, 2019
Xiang Zhang, Lina Yao, Manqing Dong, Zhe Liu, Yu Zhang, Yong Li

Figure 1 for Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection
Figure 2 for Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection
Figure 3 for Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection
Figure 4 for Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection

  Access Paper or Ask Questions

Searching for Interaction Functions in Collaborative Filtering


Jun 28, 2019
Quanming Yao, Xiangning Chen, James Kwok, Yong Li

Figure 1 for Searching for Interaction Functions in Collaborative Filtering
Figure 2 for Searching for Interaction Functions in Collaborative Filtering
Figure 3 for Searching for Interaction Functions in Collaborative Filtering
Figure 4 for Searching for Interaction Functions in Collaborative Filtering

  Access Paper or Ask Questions

LambdaOpt: Learn to Regularize Recommender Models in Finer Levels


May 28, 2019
Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang

Figure 1 for LambdaOpt: Learn to Regularize Recommender Models in Finer Levels
Figure 2 for LambdaOpt: Learn to Regularize Recommender Models in Finer Levels
Figure 3 for LambdaOpt: Learn to Regularize Recommender Models in Finer Levels
Figure 4 for LambdaOpt: Learn to Regularize Recommender Models in Finer Levels
* Accepted by KDD 2019 
  Access Paper or Ask Questions

Learning Phase Competition for Traffic Signal Control


May 12, 2019
Guanjie Zheng, Yuanhao Xiong, Xinshi Zang, Jie Feng, Hua Wei, Huichu Zhang, Yong Li, Kai Xu, Zhenhui Li

Figure 1 for Learning Phase Competition for Traffic Signal Control
Figure 2 for Learning Phase Competition for Traffic Signal Control
Figure 3 for Learning Phase Competition for Traffic Signal Control
Figure 4 for Learning Phase Competition for Traffic Signal Control

  Access Paper or Ask Questions

A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks


Jan 20, 2019
Long Zhang, Xuechao Sun, Yong Li, Zhenyu Zhang

Figure 1 for A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks
Figure 2 for A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks
Figure 3 for A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks
Figure 4 for A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks

  Access Paper or Ask Questions