Kun Zhang (张琨)

Kun Zhang (张琨)

Hefei University of Technology (HFUT)

🎓About Me

I am an associate professor and doctoral supervisor 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.

【Opening Position】I am looking forward Ph.D. students for Large Language Models research.

I am also looking forward self-motivated students to join us. If you are interested in my research, feel free to contact 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

2024-11-05：🎉🎉 Two of my master’s students got Natural Scholarship of 2024

2024-09-05：🎉🎉 One paper on Parameter-Efficient Fine-Tuning (PEFT) got accepted by Frontiers of Computer Science (FCS)

2024-09-01：🎉 One paper on Contrastive Representation Learning got accepted by IEEE Transactions on Computational Social Systems (IEEE TCSS)

2024-08-22：🎉 Our undergraduate team won National Second Prize in China Collegiate Computing Contest 2024-Big Data Challenge

2024-06-12： One paper on Debiased User Preference Modeling got accepted by Chinese Journal of Computers (计算机学报)
and one paper on Visual Question Answering got accepted by Knowledge and Information Systems

2024-05-18： One paper on Cognitive Diagnosis got accepted by KDD’2024

2024-05-01：One paper on Image Sentiment Analysis got recognized as ESI High Cited Paper 🏆

2024-04-27：Two patent for multi-modal inference technology got granted

2024-03-30：One paper on Counterfactual Fairness got accepted by ACM TOIS

2024-02-26：One paper on causal-based debiasing got accepted by AI Open.

📝 Highlighted Research

Sentence Semantic Representation

AAAI 2019
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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.
IEEE TNNLS2023
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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

AI Open 2024
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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.

Representative Papers

In the year of 2024:

  • NeurIPS 2024 Workshop on M3L Increasing Fairness via Combination with Learning Guarantees. [Paper]
    Yijun Bian, Kun Zhang.

  • IEEE TCSS2024 EMCRL: EM-enhanced Negative Sampling Strategy for Contrastive Representation Learning. [Paper]
    Kun Zhang*, Guangyi Lv, Le Wu, Richang Hong, Meng Wang.

  • FCS 2024 Optimizing Low-Rank Adaptation with Decomposed Matrices and Adaptive Rank Allocation. [Paper]
    Dacao Zhang, Fan Yang, Kun Zhang*, Richang Hong

  • KDD 2024 Path-Specific Causal Reasoning for Fairness-aware Cognitive Diagnosis. [Paper], [code], [slides]
    Dacao Zhang, Kun Zhang*, Le Wu, Mi Tian, Richang Hong, Meng Wang.

  • KIS2024 Caption Matters: A New Perspective for Knowledge-based Visual Question Answering. [Paper]
    Bin Feng, Shulan Ruan, Likang Wu, Huijie Liu, Kai Zhang, Kun Zhang, Qi Liu, Enhong Chen

  • 计算机学报2024 从众性感知的因果去偏新闻推荐方法. [Paper]
    鲍纪敏, 张琨*, 吴乐, 洪日昌, 汪萌

  • ACM TOIS2024 Average User-side Counterfactual Fairness for Collaborative Filtering. [Paper]
    Pengyang Shao, Le Wu*, Kun Zhang, Defu Lian, Richang Hong, Yong Li, Meng Wang.

  • AI Open2024 Label-aware Debiased Causal Reasoning for Natural Language Inference. [Paper],
    Kun Zhang*, Dacao Zhang, Le Wu, Richang Hong, Ye Zhao, Meng Wang.

  • WWWJ2024 A relation-aware representation approach for the question matching system. [Paper],
    Yanmin Chen, Enhong Chen, Kun Zhang, Qi Liu, Ruijun Sun.

In the year of 2023:

  • IEEE TNNLS2023 Description-Enhanced Label Embedding Contrastive Learning for Text Classification. [Paper],
    Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang.

  • IEEE TKDE2023 Hyperbolic Graph Learning for Social Recommendation. [Paper],
    Yonghui Yang, Le Wu, Kun Zhang, Richang Hong, Hailin Zhou, Zhiqiang Zhang, Jun Zhou, Meng Wang.

  • IEEE TBD2023 Unified Representation Learning for Discrete Attribute Enhanced Completely Cold-Start Recommendation. [Paper]
    Haoyue Bai, Min Hou, Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Meng Wang.

  • NeurIPS2023 Disentangling Cognitive Diagnosis with Limited Exercise Labels. [Paper][EduStudio Project]
    Xiangzhi Chen, Le Wu, Fei Liu, Lei Chen, Kun Zhang, Richang Hong, Meng Wang.

  • SIGIR2023 Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation. [Paper]
    Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, Richang Hong, Meng Wang.

  • SIGIR2023 Generative-Contrastive Graph Learning for Recommendation. [Paper]
    Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang.

  • WWW2023 Improving Recommendation Fairness via Data Augmentation. [Paper]
    Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou and Meng Wang.

  • AAAI2023 Fair Representation Learning for Recommendation: A Mutual Information-Based Perspective. [Paper]
    Chen Zhao, Le Wu, Pengyang Shao, Kun Zhang, Richang Hong, Meng Wang.

  • MM2023 GoRec: A Generative Cold-start Recommendation Framework. [Paper]
    Haoyue Bai, Min Hou, Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Meng Wang.

  • 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. [Paper]
    张大操, 张琨, 吴乐, 汪萌

In the year of 2022:

  • ACM TOMM2022 PEDM: A Multi-task Learning Model for Persona-aware Emoji-embedded Dialogue Generation. [Paper], Sirui Zhao, Hongyu Jiang, Hanqing Tao, Rui Zha, Kun Zhang, Tong Xu, Enhong Chen.

  • IEEE TKDE2022 Learning from Ideography and Labels: A Schema-aware Radical-guided Associative Model for Chinese Text Classification. [Paper]
    Hanqing Tao, Guanqi Zhu, Enhong Chen, Shiwei Tong, Kun Zhang, Tong Xu, Qi Liu, Yew-Soon Ong.

  • IEEE TNNLS2022 LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching. [Paper]
    Kun Zhang, Guangyi Lv,Le Wu, Enhong Chen, Qi Liu, Meng Wang.

  • IEEE TKDE2022(🏆 ESI Highly Cited Paper) A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation. [Paper]
    Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang.

  • IEEE TAFFC2022 Causal Narrative Comprehension: A New Perspective for Emotion Cause Extraction. [Paper]
    Wei Cao; Kun Zhang; Shulan Ruan; Hanqing Tao; Sirui Zhao; Hao Wang; Qi Liu; Enhong Chen.

  • IEEE TMM2022(🏆 ESI Highly Cited Paper) Color Enhanced Cross Correlation Net for Image Sentiment Analysis. [Paper]
    Shulan Ruan, Kun Zhang, Le Wu, Tong Xu, Qi Liu, Enhong Chen.

  • IEEE TBD2022 Understanding the Users and Videos by Mining a Novel Danmu Dataset. [Paper]
    Guangyi Lv, Kun Zhang, Le Wu, Enhong Chen, Tong Xu, Qi Liu, Weidong He.

  • ACL2022 Findings Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis. [Paper]
    Kai Zhang, Kun Zhang, Mengdi Zhang, Hongke Zhao, Qi Liu,Wei Wu, Enhong Chen.

  • SIGIR2022 Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification. [Paper]
    Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen.

  • SIGIR2022 A Review-aware Graph Contrastive Learning Framework for Recommendation. [Paper]
    Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li.

In the year of 2021:

  • IEEE TSMC:S2021 Multi-Level Image-Enhanced Sentence Representation Net for Natural Language Inference. [Paper]
    Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, Han Wu, Xing Xie, Fangzhao Wu.

  • AAAI2021 Making the relation matters: Relation of relation learning network for sentence semantic matching. [Paper]
    Kun Zhang, Le Wu, Guangyi Lv, Meng Wang, Enhong Chen, Shulan Ruan.

  • ICCV2021 DAE-GAN- Dynamic Aspect-aware GAN for Text-to-Image Synthesis. [Paper]
    Shulan Ruan, Yong Zhang, Kun Zhang, Yanbo Fan, Fan Tang, Qi Liu, Enhong Chen.

  • SIGIR2021 Privileged Graph Distillation for Cold Start Recommendation. [Paper]
    Shuai Wang, Kun Zhang, Le Wu, Haiping Ma, Richang Hong, Meng Wang.

  • 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. [Paper]
    张琨，吕广奕，吴乐，刘淇，陈恩红.

In the year before 2021:

  • AAAI2020 Revisiting graph based collaborative filtering A linear residual graph convolutional network approach. [Paper]
    Lei Chen, Le Wu, Richang Hong, Kun Zhang, Meng Wang.

  • SIGIR2020 Joint item recommendation and attribute inference An adaptive graph convolutional network approach. [Paper]
    Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Yanjie Fu, Meng Wang.

  • WWW2020 Dual learning for explainable recommendation Towards unifying user preference prediction and review generation. [Paper]
    Peijie Sun, Le Wu, Kun Zhang, Yanjie Fu, Richang Hong, Meng Wang.

  • ICME2020 Context-Awar Generation-Based Net For Multi-Label Visual Emotion Recognition. [Paper]
    Shulan Ruan, Kun Zhang, Yijun Wang, Hanqing Tao, Weidong He, Guangyi Lv,Enhong Chen.

  • AAAI2019 DRr-Net: Dynamic Re-read Network for Sentence Semantic Matching. [Paper]
    Kun Zhang, Guangyi Lv, Linyuan Wang, Le Wu, Enhong Chen, Fangzhao Wu, and Xing Xie.

  • KDD2018 (Best Student Paper Award of Research Track) XiaoIce Band A Melody and Arrangement Generation Framework for pop music. [Paper]
    Hongyuan Zhu, Qi Liu, Nicholas Jing Yuan, Chuan Qin, Jiawei Li, Kun Zhang, Guang Zhou, Furu Wei, Yuanchun Xu, Enhong Chen.

  • ICDM2018 Image-Enhanced Multi-Level Sentence Representation Net for Natural Language Inference. [Paper]
    Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, and Han Wu.

  • AAAI2017 A Context-Enriched Neural Network method for Recognizing Lexical Entailment. [Paper]
    Kun Zhang, Enhong Chen, Qi Liu, Chuanren Liu, and Guangyi Lv.

💬 Invited Talk

  • 2024-10-13: Give talks on “Label-aware Debiased Causal Reasoning for Natural Language Inference” at SMP2024.

  • 2023-11-24: Give talks on “Causally Inspired Debiased model learning and inference” at the Workshop at SMP2023.

  • 2023-05-19: Given talks on “Text Enriched Personalized User Modeling and Explanable Recommendation” at CCF YEF2023.

  • 2023-03-20: Given talks on “Knowledge Inspired Text Representation and Reasoning” at Anhui Artificial Intelligence Society Annual Conference

🥇 Honors and Awards

  • 2024.08 National Second Prize in China Collegiate Computing Contest 2024-Big Data Challenge
  • 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.

🤝 Collaborators