• Hongshen Young Faculty
• Name (Simplified Chinese):Beibei Li
• Name (English):Beibei Li
• Name (Pinyin):libeibei
• E-Mail:6efb981898a92b76d34009e735a2d9a77dd7e620a27d247a06e61a0925b3a2a2815cb766a1f03053dff5818d1ea4d367aedf39dd87998706cbe79653a4b189c4e57287aea9bf81ecf827b28cc3230d1cb413eda8007f6a8d61dfeb49ecdee0ce77f46ce384537add530eb4daf6ffbbb45a04441c707f63e0b171df683f335b1a
• Date of Employment:2022-07-01
• School/Department:计算机学院
• Education Level:With Certificate of Graduation for Doctorate Study
• Business Address:信息科研楼 B606-3
• Gender:Female
• Contact Information:libeibeics@cqu.edu.cn
• Degree:Doctoral degree
• Status:Employed
• Alma Mater:中国科学院大学

• No content

👩‍💻 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：（多模态）大语言模型：个性化、智能体、幻觉、安全、长程记忆、知识编辑AI+医疗：智慧问诊，医疗知识库信息检索：Agentic检索，多模态检索，垂域知识库，推荐系统其他：数据挖掘，受限数据下的机器学习（弱监督学习）本课题组长期招聘本科生研究助理，有老师/学长学姐手把手指导欢迎学有余力、有自驱力和科研兴趣的同学 邮件联系我（libeibeics@cqu.edu.cn, 请附带成绩单和简历）🎓 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2012.09 - 2016.07, 重庆大学，软件学院，软件工程，本科🔥 动态2025.11: 受邀在期刊 Information (JCR Q2) 上组织了一期关于 *弱监督学习* 的特刊，欢迎赐稿（截稿日期2026年7月31日）, https://www.mdpi.com/journal/information/special_issues/R7WW236KU92025.11: 🎉 一篇论文被 AAAI (AAAI Conference on Artificial Intelligence, CCF-A) 2026 接收。2025.05: 🎉 受邀担任 CCF-B 会议 DASFAA Session Chair。2025.03: 🎉 两篇论文被 DASFAA (International Conference on Database Systems for Advanced Applications, CCF-B) 2025 接收。2024.09: 🎉 一篇论文被 TIST (ACM Transactions on Intelligent Systems and Technology) 接收。2024.08: 🎉 一篇论文被 TIST (ACM Transactions on Intelligent Systems and Technology) 接收。2024.07: 🎉 一篇论文被 SCIS (Science China Information Sciences, CCF-A) 接收。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。📝 部分已发表论文第一作者/第一通讯作者发表的代表性论文如下[1] Jiayu Hu, Jiangwei Xia, Beibei Li, Yanjun Qin, Bing Ji, Zhongshi He. 2026. Look Closer! An Adversarial Parametric Editing Framework for Hallucination Mitigation in VLMs. In the proceedings of the 50th AAAI Conference on Artificial Intelligence (AAAI’26). (CCF-A 会议，唯一通讯作者)[2] Beibei Li, Yiyuan Zheng, Beihong Jin, Tao Xiang, Haobo Wang, and Lei Feng. 2025. AsyCo: an asymmetric dual-task co-training model for partial-label learning. SCIENCE CHINA Information Sciences. 68, 5 (SCIS’25). (CCF-A 期刊，第一作者) [3] Beibei Li, Beihong Jin, Jiageng Song, Yisong Yu, Yiyuan Zheng, and Wei Zhou. 2022. Improving Micro-video Recommendation via Contrastive Multiple Interests. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22). (CCF-A会议，第一作者)[4] Beibei Li, Tao Xiang, Beihong Jin, Yiyuan Zheng, Rui Zhao. 2025. Semantic Gaussian Mixture Variational Autoencoder for Sequential Recommendation. Accepted by the 30th International Conference on Database Systems for Advanced Applications (DASFAA’25). (CCF-B会议，第一作者)[5] Zhifang Zhang, Yuwei Niu, Xin Liu, Beibei Li*. 2025. Tuning Vision-Language Models with Candidate Labels by Prompt Alignment. Accepted by the 30th International Conference on Database Systems for Advanced Applications (DASFAA’25). (CCF-B会议，唯一通讯作者)[6] Jiayu Hu, Senlin Shu, Beibei Li*, Tao Xiang, and Zhongshi He. 2024. An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes. ACM Transactions on Intelligent Systems and Technology. 15, 6 (TIST 2024). (JCR Q1 期刊，唯一通讯作者)[7] Shengjie Zhou, Senlin Shu, Haobo Wang, Hongxin Wei, Tao Xiang, and Beibei Li*. 2024. Multiple-Instance Learning from Pairwise Comparison Bags. ACM Transactions on Intelligent Systems and Technology. 15, 6 (TIST 2024). (JCR Q1 期刊，唯一通讯作者) [8] Beibei Li, Beihong Jin, Yisong Yu, Yiyuan Zheng, Jiageng Song, Wei Zhuo, and Tao Xiang. 2024. Orthogonal Hyper-category Guided Multi-interest Elicitation for Micro-video Matching. In 2024 IEEE International Conference on Multimedia and Expo (ICME’24). (CCF-B会议，第一作者)[9] Xinyu Zhang+, Beibei Li+ and Beihong Jin. Denoising Long- and Short-term Interests for Sequential Recommendation. In Proceedings of the 2024 SIAM International Conference on Data Mining (SDM’24). (CCF-B会议，共同第一作者)[10] Beibei Li, Senlin Shu, Beihong Jin, Tao Xiang, Yiyuan Zheng. 2023. Gemini: A Dual-Task Co-training Model for Partial Label Learning. Australasian Joint Conference on Artificial Intelligence (AJCAI’23) .(第一作者)[11] Beibei Li, Beihong Jin, Xinzhou Dong, Wei Zhuo. 2021. MULTIPLE: Multi-level User Preference Learning for List Recommendation. In International Conference on Web Information Systems Engineering (WISE’21). (CCF-C会议，第一作者) [12] Beibei Li, Beihong Jin, Taofeng Xue, Kunchi Liu, Qi Zhang, and Sihua Tian. 2020. Cold-Start Recommendation for On-Demand Cinemas. In Machine Learning and Knowledge Discovery in Databases (ECML-PKDD’19). (CCF-B会议，第一作者)[13] Beibei Li, Beihong Jin, Xinzhou Dong, Wei Zhuo. 2021. List Recommendation via Co-attentive User Preference Fine-Tuning. International Conference on Neural Information Processing (ICONIP’21). (CCF-C会议，第一作者) 其他作者代表性论文列表如下：[1] Yiyuan Zheng, Beibei Li, Beihong Jin, Rui Zhao, Weijiang Lai, and Tao Xiang. 2024. Multi-Intent Driven Contrastive Sequential Recommendation. In Machine Learning and Knowledge Discovery in Databases (ECML-PKDD’24). (CCF-B会议)[2] Yiyuan Zheng, Beihong Jin, Beibei Li, Weijiang Lai, Tao Xiang. 2024. Reducing Interaction Noise for Sequential Recommendation via Robust Interests. In proceedings of the 30th International Conference on Database Systems for Advanced Applications (DASFAA’24). (CCF-B会议)[3] Weijiang Lai, Beihong Jin, Beibei Li, Yiyuan Zheng, Tao Xiang. 2024. A vlogger-augmented graph neural network model for micro-video recommendation. In Machine Learning and Knowledge Discovery in Databases (ECML-PKDD’23). (CCF-B会议) [4] Yisong Yu, Beihong Jin, Jiageng Song, Beibei Li, Yiyuan Zheng, Wei Zhuo. 2022. Improving micro-video recommendation by controlling position bias. In Machine Learning and Knowledge Discovery in Databases (ECML-PKDD’22). (CCF-B会议)[5] Xinzhou Dong, Beihong Jin, Wei Zhuo, Beibei Li, Taofeng Xue. 2021. Sirius: sequential recommendation with feature augmented graph neural networks. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (DASFAA’21). (CCF-B会议) [6] Xinzhou Dong, Beihong Jin, Beibei Li, Taofeng Xue. 2021. Improving sequential recommendation with attribute-augmented graph neural networks. In Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’21). (CCF-C会议)[7] Taofeng Xue, Beihong Jin, Beibei Li, Weiqing Wang, Qi Zhang, and Sihua Tian. 2019. A Spatio-Temporal Recommender System for On-Demand Cinemas. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM’19). (CCF-B会议) [8] Taofeng Xue, Beihong Jin, Beibei Li, Qi Zhang, and Sihua Tian. 2019. Spatial-temporal recommendation for on-demand cinemas. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (DASFAA’19). (CCF-B 会议) 查阅完整论文列表，请访问我的谷歌学术。🛸 项目国家自然科学基金委员会， 面上项目， 面向鲁棒-安全-高效协同的联邦学习聚合范式研究， 2026-01-01 至 2029-12-31，50 万元，在研，参与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”，2023.01 - 2025.12, 20 万元，在研，负责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”， 2021.01 - 2024.12, 54 万元，结题，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”，2019.01 - 2021.12, 30 万元，结题，参与企业委托合作开发项目，“智能点播影院推荐算法开发”，2018.5-2019.3，技术骨干。企业委托合作开发项目，“基于用户行为分析的智能视频推荐算法开发”，2021.7-2022.9，技术骨干。企业委托合作开发项目，“面向在线视频的智能推荐算法开发”，2019.7-2020.9，技术骨干。💻 学术服务2025.08 - 至今，中文信息学会信息检索专委会，通讯委员2022.09 - 至今, 中国计算机学会（CCF）普适计算专委会，执行委员长期担任 AAAI，IJCAI, NeurIPS, ACM MM，CIKM, TNNLS，PR 等国际期刊和会议（高级）审稿人担任 DASFAA 2025 Session Chair