贾林瀚 @ 南京大学计算机学院 LAMDA研究所
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贾林瀚 Lin-Han Jia
博士研究生 导师: 李宇峰教授 实验室: 南京大学仙林校区计算机科学楼 912 室 |
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教育经历
2022年至今，于南京大学计算机学院免试直接攻读博士学位，师从李宇峰教授，加入由周志华院士创立的机器学习与数据挖掘（LAMDA）研究所。
2018-2022年，于吉林大学计算机科学与技术学院获学士学位，加入由王湘浩院士创立的符号计算与知识工程教育部重点实验室。
研究方向
主要研究自监督、半监督、弱监督、无监督学习，同时深耕知识数据双驱动学习范式，聚焦充分利用无标注数据和先验知识的模型训练基础研究。
具体兴趣点包括：
- 预训练与下游任务的内在关联性：明确各种无监督预训练方法的能力边界，研究现有基础模型在下游目标中的局限性与预训练数据与任务本身的关联。
- 预训练数据选择与合成：构建基于下游目标和先验知识的训练数据选择与合成系统，形成任务端到数据端的的动态反馈机制，基于语义向量模型和向量库优化实现大规模训练数据管理。
- 可量化的训练决策框架：建立针对模型训练决策过程的量化框架，实现在高成本训练前量化估计训练决策收益，降低大规模训练的时间与算力成本。
- 预训练数据与任务工作流推理：推动训练框架自动化由搜索范式向推理范式转移，实现训练数据管道和训练任务流程自适应设计。
论文
会议论文
Lin-Han Jia, Si-Yu Han, Wen-Chao Hu, Jie-Jing Shao, Wen-Da Wei, Zhi Zhou, Lan-Zhe Guo, Yu-Feng Li. Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning. In: Proceedings of the 43rd International Conference on Machine Learning (ICML'26). 2026. CCF-A. [Paper][Code]
Hong-Jie You, Jie-Jing Shao, Xiao-Wen Yang, Lin-Han Jia, Lan-Zhe Guo, Yu-Feng Li. Pianist Transformer: Towards Expressive Piano Performance Rendering via Scalable Self-Supervised Pre-Training. In: Proceedings of the 43rd International Conference on Machine Learning (ICML'26). 2026. CCF-A. [Paper]
Hong-Jie You, Jie-Jing Shao, Xiao-Wen Yang, Zhi-Fan Wu, Lin-Han Jia, Lan-Zhe Guo, Yu-Feng Li. FormalImG: Evaluating Structural Compositional Generalization for T2I Models. In: Proceedings of the 43rd International Conference on Machine Learning (ICML'26) Workshop on Combining Theory and Benchmarks: Towards A Virtuous Cycle to Understand and Guarantee Foundation Model Performance. 2026. [Paper]
Wen-Chao Hu, Qi-Jie Li, Lin-Han Jia, Cunjing Ge, Yu-Feng Li, Yuan Jiang, Zhi-Hua Zhou. Curriculum Abductive Learning. In: the 39th Annual Conference on Neural Information Processing Systems (NeurIPS'25). 2025. CCF-A. [Paper]
Shi-Yu Tian, Zhi Zhou, Kun-Yang Yu, Ming Yang, Lin-Han Jia, Lan-Zhe Guo, Yu-Feng Li. VC Search: Bridging the Gap Between Well-Defined and Ill-Defined Problems in Mathematical Reasoning. In: Proceedings of the 30th Conference on Empirical Methods in Natural Language (EMNLP'25). 2025. CCF-B. Oral Presentation. [Paper]
Si-Yu Han, Lin-Han Jia, Yu-Feng Li. 基于正则的稳健数据重载量子学习模型. In: Proceedings of the 20th Chinese Conference on Machine Learning (CCML'25). 2025. Best Paper Award Nomination.
Lin-Han Jia, Wen-Chao Hu, Jie-Jing Shao, Lan-Zhe Guo, Yu-Feng Li. Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible. In: Proceedings of the 42nd International Conference on Machine Learning (ICML'25). 2025. CCF-A. [Paper][Code]
Xiao-Wen Yang, Jie-Jing Shao, Lan-Zhe Guo, Bo-Wen Zhang, Zhi Zhou, Lin-Han Jia, Wang-Zhou Dai, Yu-Feng Li. Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models. In: Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI'2025 Survey Track). 2025. CCF-B. [Paper]
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, and Yu-Feng Li. Realistic Evaluation of Semi-Supervised Learning Algorithms in Open Environments. In: Proceedings of the 12th International Conference on Learning Representations (ICLR'24). 2024. CCF-A. Spotlight Presentation. [Paper][Code]
Zhi-Zhou, Lan-Zhe Guo, Lin-Han Jia, Ding-Chu Zhang, Yu-Feng Li. ODS: Test-Time Adaptation in the Presence of Open-World Data Shift. In: Proceedings of the 40th International Conference on Machine Learning (ICML'23). 2023. CCF-A. Oral Presentation. [Paper]
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yuke Xiang, Yu-Feng Li. Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions. In: Proceedings of the 40th International Conference on Machine Learning (ICML'23). 2023. CCF-A. Oral Presentation. [Paper][Code]
Lan-Zhe Guo, Lin-Han Jia, Jie-Jing Shao, Yu-Feng Li. Robust Semi-Supervised Learning in Open Environments. Frontiers of Computer Science. 2025. CCF-B. [Paper]
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, and Yu-Feng Li. LAMDA-SSL: A Comprehensive Semi-Supervised Learning Toolkit. Science CHINA Information Science. 2023. CCF-A. [Paper][Code][Slide]
Lin-Han Jia, Jie-Jing Shao, Wen-Chao Hu, Zhi Zhou, Lan-Zhe Guo, Yu-Feng Li. Learning Task Design Based on Fuzzy Logical Reasoning. 2026. [Paper]
Wen-Chao Hu, Lin-Han Jia, Cunjing Ge, Yu-Feng Li, Yuan Jiang, and Zhi-Hua Zhou. ABL-Forest: Localized Abductive Learning with Formal Guarantees. 2026.
Rui-Zhi Qin, Jie-Jing Shao, Xiao-Wen Yang, Lin-Han Jia, Lan-Zhe Guo, Yu-Feng Li. COAST: Self-Correction Learning for Mastering Constraint Satisfaction in Travel Planning. 2026.
Lin-Han Jia, Si-Yu Han, Lan-Zhe Guo, Zhi Zhou, Zhao-Long Li, Yu-Feng Li, Zhi-Hua Zhou. A Smooth Transition Between Induction and Deduction: Fast Abductive Learning Based on Probabilistic Symbol Perception. arXiv preprint arXiv:2502.12919. 2025. [Paper]
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Si-Yu Han, Zi-Wen Li, Yu-Feng Li. Detecting Scarce and Sparse Anomalous: Solving Dual Imbalance in Multi-Instance Learning. arXiv preprint arXiv:2503.13562. 2025. [Paper]
Si-Yu Han, Lin-Han Jia, Lan-Zhe Guo. Multiple Embeddings for Quantum Machine Learning. arXiv preprint arXiv:2503.22758. 2025. [Paper]
CCF博士生资助计划（全国共10人），2026年
CCML最佳论文提名奖，2025年
LAMDA英才奖（共3人），2025年
精英博士奖学金，2024年
国家奖学金，2023年
优秀研究生，2023-2025年
优秀本科毕业生，2022年
优秀本科毕业论文，2022年
CCF优秀大学生（全国共94人），2021年
ACM-ICPC国际大学生程序设计竞赛亚洲区域赛，银牌，2021年
CCPC中国大学生程序设计竞赛省赛，金牌，2020年
美国大学生数学建模竞赛Finalist奖（特等奖提名，全球前1.5%），2020年
全国大学生数学建模竞赛省赛，一等奖，2019年
- Lead contributor to LAMDA-SSL, a semi-supervised learning toolkit, with over 29,000 downloads via pip. [Project] [Documentation] [Examples]
- Contributor to ABLkit, an abductive learning toolkit, with over 22,000 downloads via pip. [Project] [Documentation] [Examples]
- 学术会议高级委员会成员: IJCAI 2025
- 学术会议委员会成员: NeurIPS 2023-2025、AAAI 2024-2026、ICLR 2024-2026、IJCAI 2024-2026、ICML 2025-2026、KDD 2024-2026、CVPR 2026、 ECCV 2026
- 学术会议志愿者: IJCLR 2024, MLA 2022-2023
- 期刊审稿人: Machine Learning, Neuro Computing, Neural Networks
- 教学助理: 高级机器学习（南京大学，面向研究生），2024-2025年