Shen Wang

According to our database, Shen Wang authored at least 44 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

UniEDU: A Unified Language and Vision Assistant for Education Applications.

Zhendong Chu, Jian Xie, Shen Wang, Zichao Wang, Qingsong Wen

CoRR, March, 2025

MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection.

Yibo Yan, Shen Wang, Jiahao Huo, Philip S. Yu, Xuming Hu, Qingsong Wen

CoRR, March, 2025

LLM Agents for Education: Advances and Applications.

Zhendong Chu, Shen Wang, Jian Xie, Tinghui Zhu, Yibo Yan, Jinheng Ye, Aoxiao Zhong, Xuming Hu, Jing Liang, Philip S. Yu, Qingsong Wen

CoRR, March, 2025

Corrections Meet Explanations: A Unified Framework for Explainable Grammatical Error Correction.

Jingheng Ye, Shang Qin, Yinghui Li, Hai-Tao Zheng, Shen Wang, Qingsong Wen

CoRR, February, 2025

Position: LLMs Can be Good Tutors in Foreign Language Education.

Jingheng Ye, Shen Wang, Deqing Zou, Yibo Yan, Kun Wang, Hai-Tao Zheng, Zenglin Xu, Irwin King, Philip S. Yu, Qingsong Wen

CoRR, February, 2025

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning.

Yibo Yan, Shen Wang, Jiahao Huo, Jingheng Ye, Zhendong Chu, Xuming Hu, Philip S. Yu, Carla P. Gomes, Bart Selman, Qingsong Wen

CoRR, February, 2025

A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges.

Yibo Yan, Jiamin Su, Jianxiang He, Fangteng Fu, Xu Zheng, Yuanhuiyi Lyu, Kun Wang, Shen Wang, Qingsong Wen, Xuming Hu

Proceedings of the Findings of the Association for Computational Linguistics, 2025

AI-Driven Virtual Teacher for Enhanced Educational Efficiency: Leveraging Large Pretrain Models for Autonomous Error Analysis and Correction.

Tianlong Xu, Yifan Zhang, Zhendong Chu, Shen Wang, Qingsong Wen

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges.

Yibo Yan, Jiamin Su, Jianxiang He, Fangteng Fu, Xu Zheng, Yuanhuiyi Lyu, Kun Wang, Shen Wang, Qingsong Wen, Xuming Hu

CoRR, 2024

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection.

Yibo Yan, Shen Wang, Jiahao Huo, Hang Li, Boyan Li, Jiamin Su, Xiong Gao, Yifan Zhang, Tianlong Xu, Zhendong Chu, Aoxiao Zhong, Kun Wang, Hui Xiong, Philip S. Yu, Xuming Hu, Qingsong Wen

CoRR, 2024

Large Language Models for Education: A Survey and Outlook.

Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen

CoRR, 2024

Revisit Orthogonality in Graph-Regularized MLPs.

Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

STREET: A Multi-Task Structured Reasoning and Explanation Benchmark.

Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Henry Zhu, Rui Dong, Deguang Kong, Juliette Burger, Anjelica Ramos, William Yang Wang, Zhiheng Huang, George Karypis, Bing Xiang, Dan Roth

CoRR, 2023

OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization.

Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu

CoRR, 2023

Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs.

Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

STREET: A Multi-Task Structured Reasoning and Explanation Benchmark.

Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Henghui Zhu, Rui Dong, Deguang Kong, Juliette Burger, Anjelica Ramos, Zhiheng Huang, William Yang Wang, George Karypis, Bing Xiang, Dan Roth

Proceedings of the Eleventh International Conference on Learning Representations, 2023

IGCN: Item Influence Enhanced Graph Convolution Networks for Recommendation of Cold-Start Items.

Shen Wang, Ziwei Fan, Jibing Gong, Xiaokai Wei, Philip S. Yu

Proceedings of the IEEE International Conference on Data Mining, 2023

NameGuess: Column Name Expansion for Tabular Data.

Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

TRANSGNN: Towards Knowledge Enhanced Top-K Recommendation via Transformed Heterogeneous Graph Neural Network.

Shen Wang, Ziwei Fan, Jibing Gong, Xiaokai Wei, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2023

Automatic Table Union Search with Tabular Representation Learning.

Xuming Hu, Shen Wang, Xiao Qin, Chuan Lei, Zhengyuan Shen, Christos Faloutsos, Asterios Katsifodimos, George Karypis, Lijie Wen, Philip S. Yu

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Debiasing Neural Retrieval via In-batch Balancing Regularization.

Yuantong Li, Xiaokai Wei, Zijian Wang, Shen Wang, Parminder Bhatia, Xiaofei Ma, Andrew O. Arnold

CoRR, 2022

Entailment Tree Explanations via Iterative Retrieval-Generation Reasoner.

Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Rui Dong, Xiaokai Wei, Henry Zhu, Xinchi Chen, Zhiheng Huang, Peng Xu, Andrew O. Arnold, Dan Roth

CoRR, 2022

Entailment Tree Explanations via Iterative Retrieval-Generation Reasoner.

Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Rui Dong, Xiaokai Wei, Henghui Zhu, Xinchi Chen, Peng Xu, Zhiheng Huang, Andrew O. Arnold, Dan Roth

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System.

Shen Wang, Liangwei Yang, Jibing Gong, Shaojie Zheng, Shuying Du, Zhiwei Liu, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2022

Towards Robust Graph Neural Networks via Adversarial Contrastive Learning.

Shen Wang, Zhengzhang Chen, Jingchao Ni, Haifeng Chen, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Knowledge Enhanced Pretrained Language Models: A Compreshensive Survey.

Xiaokai Wei, Shen Wang, Dejiao Zhang, Parminder Bhatia, Andrew O. Arnold

CoRR, 2021

Mixed-Curvature Multi-Relational Graph Neural Network for Knowledge Graph Completion.

Shen Wang, Xiaokai Wei, Cícero Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang, Philip S. Yu, Isabel F. Cruz

Proceedings of the WWW '21: The Web Conference 2021, 2021

Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation.

Ziwei Fan, Zhiwei Liu, Shen Wang, Lei Zheng, Philip S. Yu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Knowledge Graph Representation via Hierarchical Hyperbolic Neural Graph Embedding.

Shen Wang, Xiaokai Wei, Cícero Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew O. Arnold, Philip S. Yu

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Generative temporal link prediction via self-tokenized sequence modeling.

Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui, Guandong Xu

World Wide Web, 2020

Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View.

Jibing Gong, Shen Wang, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

H2KGAT: Hierarchical Hyperbolic Knowledge Graph Attention Network.

Shen Wang, Xiaokai Wei, Cícero Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang, Philip S. Yu

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

Heterogeneous Graph Matching Networks.

Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, Philip S. Yu

CoRR, 2019

Adversarial Defense Framework for Graph Neural Network.

Shen Wang, Zhengzhang Chen, Jingchao Ni, Xiao Yu, Zhichun Li, Haifeng Chen, Philip S. Yu

CoRR, 2019

Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification.

Shen Wang, Zhengzhang Chen, Ding Li, Zhichun Li, Lu-An Tang, Jingchao Ni, Junghwan Rhee, Haifeng Chen, Philip S. Yu

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Heterogeneous Graph Matching Networks for Unknown Malware Detection.

Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, Philip S. Yu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Heterogeneous Graph Matching Networks: Application to Unknown Malware Detection.

Shen Wang, Philip S. Yu

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Deep Program Reidentification: A Graph Neural Network Solution.

Shen Wang, Zhengzhang Chen, Ding Li, Lu-An Tang, Jingchao Ni, Zhichun Li, Junghwan Rhee, Haifeng Chen, Philip S. Yu

CoRR, 2018

Deep Co-Investment Network Learning for Financial Assets.

Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui

Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

Market Abnormality Period Detection via Co-movement Attention Model.

Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Structural Deep Brain Network Mining.

Shen Wang, Lifang He, Bokai Cao, Chun-Ta Lu, Philip S. Yu, Ann B. Ragin

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Kernelized Support Tensor Machines.

Lifang He, Chun-Ta Lu, Guixiang Ma, Shen Wang, LinLin Shen, Philip S. Yu, Ann B. Ragin

Proceedings of the 34th International Conference on Machine Learning, 2017

Multi-way Multi-level Kernel Modeling for Neuroimaging Classification.

Lifang He, Chun-Ta Lu, Hao Ding, Shen Wang, Linlin Shen, Philip S. Yu, Ann B. Ragin

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Deep eye fixation map learning for calibration-free eye gaze tracking.

Kang Wang, Shen Wang, Qiang Ji

Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, 2016