🎓About Me
I am an assistant professor at Hefei University of Technology. Before that, I was graduated from the School of Computer Science and Technology, University of Science and Technology of China (USTC) (中国科学技术大学计算机与信息学院) with a bachelor’s degree and doctor’s degree, advised by Enhong Chen (陈恩红). I also collaborate with Qi Liu (刘淇) from University of Science and Technology of China (USTC), Le Wu (吴乐) from Hefei University of Technology (HFUT), Xing Xie (谢幸) from Microsoft Research Asia. I have been selected for the 2022 MSRA StarTrack Scholar, won the Chinese Academy of Sciences President’s Award 2019, and winner of the KDD 2018 Best Student Paper Award.
My research interests include Semantic Representation, Large Language Models, Causal Reasoning and Debiased Learning, Recommender System. I have published 30+ papers on SIGIR, ACL, WWW, AAAI, etc. If you are seeking any form of academic cooperation, please feel free to email me.
📍 Contact
- Key Laboratory of Knowledge Engineering with Big Data
- School of Computer Science and Information Engineering, School of Artificial Intelligence Hefei University of Technology (HFUT).
- Office: Room 906, Kejiao A Building, Feicui Campus of HFUT, Hefei, Anhui, China, 230601
- Email: zhang1028kun@gmail.com, zhkun@hfut.edu.cn
- Google Scholar
🔥 News
2024-04-19:🎉🎉 One patent for sentence semantic matching technology got granted
2024-03-30:🎉 One paper on Counterfactual Fairness got accepted by ACM TOIS
Average User-side Counterfactual Fairness for Collaborative Filtering
2024-02-26:🎉 One paper on causal-based debiasing got accepted by AI Open.
Label-aware Debiased Causal Reasoning for Natural Language Inference
📝 Highlighted Research
Sentence Semantic Representation
DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching
Kun Zhang, Guangyi Lv, Linyuan Wang, Le Wu, Enhong Chen, Fangzhao Wu, and Xing Xie
- This work draws inspiration from cognitive psychology and designs dynamic attention mechanism (DRr-Net) to realize the focusing and dynamic adjustment of attention, improving the quality of generated sentence representations.
- This work is also extend to IEEE TNNLS2022.
Description-Enhanced Label Embedding Contrastive Learning for Text Classification
Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang
- The previous work R$^2$-Net has been accepted by AAAI 2021
- This work proposed a novel self-supervised learning framework to make full use of label information to achieve high-quality sentence representation generation and relation inference.
Causal Inference-based Debiasing
Label-aware Debiased Causal Reasoning for Natural Language Inference
Kun Zhang*, Dacao Zhang, Le Wu, Richang Hong, Ye Zhao, Meng Wang, AI Open.
- This work proposes that label information can be used to guide the spurious correlation identification. Thus, it treats label information as one variable in causal graph and utilizes counterfactual inference to remove the spurious correlations introduced by human annotations.Finally, it realize debiased and robust natural language inference.
- We also extend this work into multi-modal scenarios and public one high-quality paper in Journal of Computer Research and Development.
💻 Selected Research Papers
* corresponding author
My full paper list can also be found at Google Scholar.
Semantic Representation Learning
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WWWJ2024
A relation-aware representation approach for the question matching system,Yanmin Chen, Enhong Chen, Kun Zhang, Qi Liu, Ruijun Sun, World Wide Web. -
IEEE TNNLS2023
Description-Enhanced Label Embedding Contrastive Learning for Text Classification, Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang, IEEE Transactions on Neural Networks and Learning Systems (JCR Q1, 10.4002) -
ACM TOMM2022
PEDM: A Multi-task Learning Model for Persona-aware Emoji-embedded Dialogue Generation, Sirui Zhao, Hongyu Jiang, Hanqing Tao, Rui Zha, Kun Zhang, Tong Xu, Enhong Chen, ACM Transactions on Multimedia Computing, Communications and Applications. -
IEEE TKDE2022
Learning from Ideography and Labels: A Schema-aware Radical-guided Associative Model for Chinese Text Classification, Hanqing Tao, Guanqi Zhu, Enhong Chen, Shiwei Tong, Kun Zhang, Tong Xu, Qi Liu, Yew-Soon Ong, IEEE Transactions on Knowledge and Data Engineering. -
IEEE TNNLS2022
LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching, Kun Zhang, Guangyi Lv,Le Wu, Enhong Chen, Qi Liu, Meng Wang, IEEE Transactions on Neural Networks and Learning Systems (JCR Q1, 10.4002). -
ACL2022 Findings
Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis, Kai Zhang, Kun Zhang, Mengdi Zhang, Hongke Zhao, Qi Liu,Wei Wu, Enhong Chen, The 60th annual meeting of the Association for Computational Linguistics. -
SIGIR2022
Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification, Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen, The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. -
IEEE TMM2022
Color Enhanced Cross Correlation Net for Image Sentiment Analysis, Shulan Ruan, Kun Zhang, Le Wu, Tong Xu, Qi Liu, Enhong Chen, IEEE Transactions on Multimedia. -
IEEE TSMC:S2021
Multi-Level Image-Enhanced Sentence Representation Net for Natural Language Inference, Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, Han Wu, Xing Xie, Fangzhao Wu, IEEE Transaction on Systems, Man, and Cybernetics: Systems. -
AAAI2021
Making the relation matters: Relation of relation learning network for sentence semantic matching, Kun Zhang, Le Wu, Guangyi Lv, Meng Wang, Enhong Chen, Shulan Ruan, Proceedings of the AAAI conference on artificial intelligence. -
ICCV2021
DAE-GAN- Dynamic Aspect-aware GAN for Text-to-Image Synthesis, Shulan Ruan, Yong Zhang, Kun Zhang, Yanbo Fan, Fan Tang, Qi Liu, Enhong Chen, Proceedings of the IEEE/CVF International Conference on Computer Vision. -
计算机学报2021
图像信息对句子语义理解与表示的有效性验证与分析, 张琨,吕广奕,吴乐,刘淇,陈恩红, 计算机学报. -
ICME2020
Context-Awar Generation-Based Net For Multi-Label Visual Emotion Recognition, Shulan Ruan, Kun Zhang, Yijun Wang, Hanqing Tao, Weidong He, Guangyi Lv,Enhong Chen, IEEE International Conference on Multimedia and Expo. -
AAAI2019
DRr-Net: Dynamic Re-read Network for Sentence Semantic Matching, Kun Zhang, Guangyi Lv, Linyuan Wang, Le Wu, Enhong Chen, Fangzhao Wu, and Xing Xie, Proceedings of the AAAI Conference on Artificial Intelligence. -
KDD2018
XiaoIce Band A Melody and Arrangement Generation Framework for pop music, Hongyuan Zhu, Qi Liu, Nicholas Jing Yuan, Chuan Qin, Jiawei Li, Kun Zhang, Guang Zhou, Furu Wei, Yuanchun Xu, Enhong Chen, The 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. (Best Student Paper Award of Research Track) -
ICDM2018
Image-Enhanced Multi-Level Sentence Representation Net for Natural Language Inference, Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, and Han Wu, IEEE International Conference on Data Mining. -
AAAI2017
A Context-Enriched Neural Network method for Recognizing Lexical Entailment, Kun Zhang, Enhong Chen, Qi Liu, Chuanren Liu, and Guangyi Lv, Proceedings of the AAAI Conference on Artificial Intelligence
User Modeling
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IEEE TKDE2023
Hyperbolic Graph Learning for Social Recommendation, Yonghui Yang, Le Wu, Kun Zhang, Richang Hong, Hailin Zhou, Zhiqiang Zhang, Jun Zhou, Meng Wang, IEEE Transactions on Knowledge and Data Engineering. -
IEEE TBD2023
Unified Representation Learning for Discrete Attribute Enhanced Completely Cold-Start Recommendation, Haoyue Bai, Min Hou, Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Meng Wang, IEEE Transactions on Big Data. -
NeurIPS2023
Disentangling Cognitive Diagnosis with Limited Exercise Labels, Xiangzhi Chen, Le Wu, Fei Liu, Lei Chen, Kun Zhang, Richang Hong, Meng Wang, Thirty-seventh Conference on Neural Information Processing Systems. EduStudio Project -
SIGIR2023
Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation, Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong, Meng Wang, The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. -
SIGIR2023
Generative-Contrastive Graph Learning for Recommendation, Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang, The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. -
AAAI2023
Fair Representation Learning for Recommendation: A Mutual Information-Based Perspective, Chen Zhao, Le Wu, Pengyang Shao, Kun Zhang, Richang Hong, Meng Wang, Proceedings of the AAAI Conference on Artificial Intelligence. -
MM2023
GoRec: A Generative Cold-start Recommendation Framework, Haoyue Bai, Min Hou, Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Meng Wang, The 31st ACM International Conference on Multimedia. -
IEEE TKDE2022
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation, Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang, IEEE Transactions on Knowledge and Data Engineering. -
SIGIR2022
A Review-aware Graph Contrastive Learning Framework for Recommendation, Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li, The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. -
IEEE TBD2022
Understanding the Users and Videos by Mining a Novel Danmu Dataset, Guangyi Lv, Kun Zhang, Le Wu, Enhong Chen, Tong Xu, Qi Liu, Weidong He, IEEE Transactions on Big Data. -
SIGIR2021
Privileged Graph Distillation for Cold Start Recommendation, Shuai Wang, Kun Zhang, Le Wu, Haiping Ma, Richang Hong, Meng Wang, The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. -
AAAI2020
Revisiting graph based collaborative filtering A linear residual graph convolutional network approach, Lei Chen, Le Wu, Richang Hong, Kun Zhang, Meng Wang, Proceedings of the AAAI conference on artificial intelligence. -
SIGIR2020
Joint item recommendation and attribute inference An adaptive graph convolutional network approach, Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Yanjie Fu, Meng Wang, Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval. -
WWW2020
Dual learning for explainable recommendation Towards unifying user preference prediction and review generation, Peijie Sun, Le Wu, Kun Zhang, Yanjie Fu, Richang Hong, Meng Wang, Proceedings of The Web Conference.
Causal Reasoning
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ACM TOIS2024
Average User-side Counterfactual Fairness for Collaborative Filtering, Pengyang Shao, Le Wu*, Kun Zhang, Defu Lian, Richang Hong, Yong Li, Meng Wang, ACM Transactions on Information Systems. -
AI Open2024
Label-aware Debiased Causal Reasoning for Natural Language Inference, Kun Zhang*, Dacao Zhang, Le Wu, Richang Hong, Ye Zhao, Meng Wang, AI Open. -
WWW2023
Improving Recommendation Fairness via Data Augmentation, Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou and Meng Wang, The web Conference. -
计算机研究与发展2023
针对情境感知的自然语言推理的因果去偏方法, 张大操, 张琨, 吴乐, 汪萌,计算机研究与发展 -
IEEE TAFFC2022
Causal Narrative Comprehension: A New Perspective for Emotion Cause Extraction, Wei Cao; Kun Zhang; Shulan Ruan; Hanqing Tao; Sirui Zhao; Hao Wang; Qi Liu; Enhong Chen, IEEE Transactions on Affective Computing.
💬 Invited Talk
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2023-11-24: Give talks on “Causally Inspired Debiased model learning and inference” ath the Workshop at SMP2023.
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2023-05-19: Given talks on “Text Enriched Personalized User Modeling and Explanable Recommendation” at CCF YEF2023.
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2023-03-20: Given talks on “Knowledge Inspired Text Representation and Reasoning” at Anhui Artificial Intelligence Society Annual Conference
🥇 Honors and Awards
- 2023.11 National Third Prize in CCIR CUP 2023
- 2023.08 National Third Prize in China Collegiate Computing Contest 2023-Big Data Challenge
- 2022.08 National Third Prize in China Collegiate Computing Contest 2022-Big Data Challenge
- 2021.10 MSRA StarTrack Scholar
- 2019.09 The president of the Chinese Academy of Sciences praises.
- 2018.07 KDD 2018 Best Student Paper Award.