Ting Long's Homepage

Ting Long 龙婷

吉林大学人工智能学院正新楼604

邮箱：longting [AT] jlu.edu.cn

研究方向：强化学习，信息检索

招生信息

招收2025年秋季入学的博士一名。对我们研究内容感兴趣的同学可以发邮件到longting [AT] jlu.edu.cn

龙婷博士现任吉林大学人工智能学院副教授、博士生导师，毕业于上海交通大学计算机科学与工程系（Apex实验室）。研究方向主要包括强化学习和信息检索，致力于将相关理论应用于推荐系统和教育场景中。龙婷博士在多个国际顶级会议上发表了多篇论文，包括ICML、KDD、AAAI、SIGIR、WSDM，ICLR等，担任AAAI、ECML/PKDD、KDD、WWW、WSDM等会议的审稿人，以及《Frontiers of Computer Science》等期刊的审稿人。

Dr. Ting Long is currently an Associate Professor and Ph.D. supervisor at the School of Artificial Intelligence, Jilin University. She received her Ph.D. from the Department of Computer Science and Engineering at Shanghai Jiao Tong University (Apex Lab). Her research interests mainly include reinforcement learning and information retrieval, with a focus on applying these theories to recommendation systems and educational scenarios. Dr. Long has published many papers in top-tier international conferences, including ICML, KDD, AAAI, SIGIR, WSDM, and ICLR. She also serves as a reviewer for prestigious conferences such as AAAI, ECML/PKDD, KDD, WWW, and WSDM, as well as journals like Frontiers of Computer Science.

Publications

HierLLM: Hierarchical Large Language Model for Question Recommendation

Yuxuan Liu, Haipeng Liu, Ting Long*

The 30th International Conference on Database Systems for Advanced Applications (DASFAA ’25)

Personalized Education with Ranking Alignment Recommendation

Haipeng Liu, Yuxuan Liu, Ting Long*

The 30th International Conference on Database Systems for Advanced Applications (DASFAA ’25)

Simulating Question-answering Correctness with a Conditional Diffusion

Ting Long, Li’ang Yin, Yi Chang, Wei Xia, Yong Yu

The ACM Web Conference (WWW ’25)

Reconstruction-Guided Policy: Enhancing Decision-Making through Agent-Wise State Consistency

Qifan Liang, Yixiang Shan, Haipeng Liu, Zhengbang Zhu, Ting Long*, Weinan Zhang

The 13th International Conference on Learning Representations (ICLR ’25)

ContraDiff: Planning Towards High Return States via Contrastive Learning

Yixiang Shan, Zhengbang Zhu, Ting Long*, Qifan Liang, Yi Chang, Weinan Zhang

The 13th International Conference on Learning Representations (ICLR ’25)

DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching

Guangxiang Li, Yixiang Shan, Zhengbang Zhu, Ting Long* Weinan Zhang

The 41st International Conference on Machine Learning (ICML ’24)

GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing

Hangyu Wang, Ting Long, Li’ang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Wei Xia, Ruiming Tang, Yong Yu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’23)

SACAT: Student-Adaptive Computerized Adaptive Testing

Jingwei Yu, Mu Zhenyu, Jiayi Lei, Li’ang Yin, Wei Xia, Yong Yu, Ting Long

Proceedings of the 5th International Conference on Distributed Artificial Intelligence (DAI ’23)

Improving Knowledge Tracing with Collaborative Information

Ting Long, Jiarui Qin, Jian Shen, Weinan Zhang, Wei Xia, Ruiming Tang, Xiuqiang He, Yong Yu

Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM ’22)

Multi-view Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection

Ting Long, Yujia Xie, Xu Chen, Weinan Zhang, Qinxiang Cao, Yong Yu

Proceedings of the AAAI Conference on Artificial Intelligence (AAAI ’22)

Automatical Graph-based Knowledge Tracing

Ting Long, Yunfei Liu, Weinan Zhang, Wei Xia, Zhicheng He, Ruiming Tang, Yong Yu

Educational Data Mining (EDM ’22)

Heterogeneous Graph Representation for Knowledge Tracing

Jisen Chen, Jian Shen, Ting Long, Liping Shen, Weinan Zhang, Yong Yu

International Conference on Neural Information Processing (ICONIP ’22)

Tracing Knowledge State with Individual Cognition and Acquisition Estimation

Ting Long, Yunfei Liu, Jian Shen, Weinan Zhang, Yong Yu

Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’21)