👩💻 工作经历
- 2022.07 - 至今, 重庆大学，计算机学院，助理研究员
- 研究兴趣：可信大模型，推荐系统，数据挖掘，弱监督学习
🎓 教育经历
- 2016.09 - 2022.07, 中国科学院大学，软件研究所，计算机软件与理论，博士，导师：金蓓弘研究员
- 2012.09 - 2016.07, 重庆大学，软件学院，软件工程，本科
🔥 最新动态
- 2024.09: 🎉 一篇论文被 TIST (ACM Transactions on Intelligent Systems and Technology) 接收，通讯作者。
- 2024.08: 🎉 一篇论文被 TIST (ACM Transactions on Intelligent Systems and Technology) 接收，通讯作者。
- 2024.07: 🎉 一篇论文被 SCIS (Science China Information Sciences, CCF-A) 接收， 第一作者。
- 2024.05: 🎉 一篇论文被 ECML PKDD (Joint European Conference on Machine Learning and Knowledge Discovery in Databases, CCF-B) 2024 接收。
- 2024.03: 🎉 一篇论文被 DASFAA (International Conference on Database Systems for Advanced Applications, CCF-B) 2024 接收。
- 2024.03: 🎉 一篇论文被 ICME (IEEE International Conference on Multimedia and Expo, CCF-B) 2024 接收。
📝 部分已发表论文
- Shengjie Zhou, Senlin Shu, Haobo Wang, Hongxin Wei, Tao Xiang, Beibei Li (通讯作者) , Multiple-Instance Learning from Pairwise Comparison Bags, ACM Transactions on Intelligent Systems and Technology, 出版中.
- Jiayu Hu, Senlin Shu, Beibei Li (通讯作者), Tao Xiang, Zhongshi He, An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes, ACM Transactions on Intelligent Systems and Technology, 出版中.
- Beibei Li, Yiyuan Zheng, Beihong Jin, Tao Xiang, Haobo Wang, Lei Feng. AsyCo: An Asymmetric Dual-task Co-training Model for Partial-label Learning, Science China Information Sciences (SCIS, CCF-A), 出版中.
- Yiyuan Zheng, Beibei Li, Beihong Jin, Rui Zhao, Weijiang Lai, Tao Xiang. Multi-intent Driven Contrastive Sequential Recommendation , Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD, CCF-B), pp. 141-156.
- Yiyuan Zheng, Beibei Li, Beihong Jin, Rui Zhao. Enhancing Sequential Recommendation via Aligning Interest Distributions , International Conference on Artificial Neural Networks, pp. 60-73.
- Yiyuan Zheng, Beihong Jin, Beibei Li, Weijiang Lai, Tao Xiang. Reducing Interaction Noise for Sequential Recommendation via Robust Interests, International Conference on Database Systems for Advanced Applications (DASFAA 2024, CCF-B), 出版中.
- Beibei Li, Beihong Jin, Yisong Yu, Yiyuan Zheng, Jiageng Song, Wei Zhuo, Tao Xiang. Orthogonal Hyper-category Guided Multi-interest Elicitation for Micro-video Matching, IEEE International Conference on Multimedia and Expo (ICME 2024, CCF-B), 出版中.
- Xinyu Zhang, Beibei Li (共同一作), Beihong Jin, Yiyuan Zheng, Rui Zhao. Denoising Long and Short-term Interests for Sequential Recommendation , SIAM International Conference on Data Mining (SDM 2024, CCF-B), pp. 544 - 552.
- Weijiang Lai, Beihong Jin, Beibei Li, Yiyuan Zheng, Rui Zhao. A Vlogger-augmented Graph Neural Network Model for Micro-video Recommendation , Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2023, CCF-B), pp. 684-699.
- Beibei Li, Senlin Shu, Beihong Jin, Tao Xiang, Yiyuan Zheng. Gemini: A Dual-task Co-training Model for Partial Label Learning , Australasian Joint Conference on Artificial Intelligence (AJCAI 2023), pp. 328-340.
- Beibei Li, Beihong Jin, Jiageng Song, Yisong Yu, Yiyuan Zheng, Wei Zhuo. Improving Micro-video Recommendation via Contrastive Multiple Interests , International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022, CCF-A), pp. 2377-2381. 代码
- Xinzhou Dong, Beihong Jin, Wei Zhuo, Beibei Li, Taofeng Xue, Jiageng Song. Modeling User Interactions by Feature-augmented Graph Neural Networks for Recommendation , CCF Transactions on Pervasive Computing and Interaction (CCF TPCI 2022), pp. 207-218.
- Yisong Yu, Beihong Jin, Jiageng Song, Beibei Li, Yiyuan Zheng, Wei Zhuo. Improving Micro-video Recommendation by Controlling Position Bias , Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2022, CCF-B), pp. 508-523.
- Beibei Li, Beihong Jin, Xinzhou Dong, Wei Zhuo. MULTIPLE: Multi-level User Preference Learning for List Recommendation , International Conference on Web Information Systems Engineering (WISE 2021, CCF-C), pp. 221-236.
- Beibei Li, Beihong Jin, Xinzhou Dong, Wei Zhuo. List Recommendation via Co-attentive User Preference Fine-Tuning , International Conference on Neural Information Processing (ICONIP 2021, CCF-C), pp. 554-562.
- Xinzhou Dong, Beihong Jin, Wei Zhuo, Beibei Li, Taofeng Xue. Sirius: Sequential Recommendation with Feature Augmented Graph Neural Networks , International Conference on Database Systems for Advanced Applications(DASFAA 2021, CCF-B), pp. 315-320.
- Xinzhou Dong, Beihong Jin, Wei Zhuo, Beibei Li, Taofeng Xue. Improving sequential recommendation with attribute-augmented graph neural networks , Pacific-Asia Conference on Knowledge Discovery and Data Mining(PAKDD 2021, CCF-C), pp. 373-385.
- Taofeng Xue, Xinzhou Dong, Wei Zhuo, Beihong Jin, He Chen, Wenhai Pan, Beibei Li, Xuejian Zhang. Feedback-guided attributed graph embedding for relevant video recommendation , Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020, CCF-B), pp. 19-35.
- Beibei Li, Beihong Jin, Taofeng Xue, Kunchi Liu, Qi Zhang, Sihua Tian. Cold-Start Recommendation for On-Demand Cinemas , Joint European Conference on Machine Learning and Knowledge Discovery in Databases(ECML PKDD 2019, CCF-B), pp. 499-515.
- Taofeng Xue, Beihong Jin, Beibei Li, Weiqing Wang, Qi Zhang, Sihua Tian. A Spatio-temporal Recommender System for On-demand Cinemas , ACM International Conference on Information and Knowledge Management(CIKM 2019, CCF-B), pp. 1553-1562.
- Taofeng Xue, Beihong Jin, Beibei Li, Kunchi Liu, Qi Zhang, Sihua Tian. Spatial-temporal Recommendation for On-demand Cinemas , International Conference on Database Systems for Advanced Applications (DASFAA 2019, CCF-B), pp. 373-377.
查阅完整论文列表，请访问我的谷歌学术。
🛸 项目
- 2023.01 - 2025.12, 负责，重庆市技术创新与应用发展专项重点项目, “新型重大突发传染病全过程全要素知识图构建关键技术研发与应用”，20 万元
- 2021.01 - 2024.12, 参与, 国家自然科学基金面上项目，“面向大规模视频推荐的用户交互行为建模”，基金号 62072450, 54 万元
- 2019.01 - 2021.12, 参与, 国家自然科学基金青年项目，“无线网络环境下的行为感知理论与关键技术”，基金号 61802373, 30 万元
🤓 学生指导
研究生
本科生
- 2023.05 - 至今, 李芷汀，重庆大学
- 2023.09 - 至今, 李宽宇，重庆大学
💻 学术服务
- 2022.09 - 至今, 中国计算机学会（CCF）普适计算专委会，委员
- 担任 DASFAA 2024 、IJCAI 2023、IJCAI 2024、HHME 2022 和 2023 审稿人
- 担任 Scientific Reports 期刊审稿人
👩🏫 教学经历
- 2022 春季, 助教, 中国科学院大学，B0911992Y 数据结构
- 2021 春季, 助教, 中国科学院大学，B0911992Y 数据结构