Xingrui Yu
About me
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Dr. Xingrui Yu is currently a research scientist in Centre for Frontier AI Research (CFAR), Agency for Science, Technology and Research (A*STAR), Singapore.
Before that, he was a Ph.D. student at Australian Artificial Intelligence Institute in University of Technology Sydney(UTS),
supervised by Prof. Ivor W. Tsang and closely collaborated with Dr. Bo Han.
His research mainly focus on:
- Trustworthy AI,
- Reinforcement Learning (RL),
- Imitation Learning (IL) and Inverse Reinforcement Learning (IRL),
- Quality Diversity Imitation Learning (QDIL),
- Embodied AI (VLAs and WAMs), and
- Agentic AI.
Opportunities
I am always looking for self-motivated student to work with me on cutting-edge research projects.
I accept CSC visiting students and research interns. I am happy to hear fom you for research collaborations.
Please feel free to drop me an email at any time.
E-mail: yu_xingrui@a-star.edu.sg
[Google Scholar]
[Github]
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News
- Six papers are accepted to ICML 2026. Congratulations to all collaborators!
- Two papers are accepted to ACL 2026 (one Main Conference, one Findings).
- One paper is accepted to ICLR 2026.
- One paper is accepted to ICML 2025.
- One paper is accepted to ICLR 2025.
- One paper is accepted to AAAI 2025.
- One paper is accepted to AAMAS 2025.
- One paper is accepted to JAIR, 2024.
Selected Publications
Chubin Zhang, Zhenglin Wan, Feng Chen, Fuchao Yang, Lang Feng, Yaxin Zhou, Xingrui Yu†, Yang You, Ivor Tsang, Bo An.
Generative Online Reinforcement Learning.
In International Conference on Machine Learning (ICML), 2026,
[PDF]. Jingxuan Wu, Zhenglin Wan, Xingrui Yu†, Yuzhe YANG, Bo An, Ivor Tsang, Yang You.
Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching.
In International Conference on Machine Learning (ICML), 2026,
[PDF]. Jie-Jing Shao, Haiyan Yin, Yueming Lyu, Xingrui Yu, Lan-Zhe Guo, Ivor Tsang, James Kwok, Yu-Feng Li.
Lifting Traces to Logic: Programmatic Skill Induction with Neuro-Symbolic Learning for Long-Horizon Agentic Tasks.
In International Conference on Machine Learning (ICML), 2026. Zhenglin Wan, Jingxuan Wu, Xingrui Yu†, Chubin Zhang, Mingcong Lei, Bo An, Ivor Tsang, Yang You.
Flow Inverse Reinforcement Learning.
In International Conference on Machine Learning (ICML), 2026,
[PDF]. Haotian Chi, Zeyu Feng, Xingrui Yu, Linbo Luo, Yew-Soon Ong, Ivor Tsang, Hechang Chen, Yi Chang, Haiyan Yin.
EvoCF: Multi-Agent Collaboration via Agentic Memory-Driven Evolutionary Counterfactual Planning.
In International Conference on Machine Learning (ICML), 2026. Binyu Zhao, Wei Zhang, Xingrui Yu†, Zhaonian Zou, Ivor Tsang.
Advancing Analytic Class-Incremental Learning through Vision-Language Calibration.
In International Conference on Machine Learning (ICML), 2026,
[PDF]. Jiawei Liu, Xun Gong, Muli Yang, Xingrui Yu, Fen Fang, Xulei Yang, Ivor Tsang, Yunfeng hu, Hong Chen, Qing Guo.
From Language to Driving: A Dual-Loop SLM-Enhanced Framework for Multi-Planner Scheduling via a Domain-Specific Language.
In Annual Meeting of the Association for Computational Linguistics (ACL), 2026. Bin Wang, Jiazheng Quan, Xingrui Yu†, Hansen Hu, Hao Yu, Anjun Gao, Zhenglin Wan, Hui Li, Ivor Tsang.
Safety Sidecar: Reflection-Driven Runtime Control for Safer Agents.
In Annual Meeting of the Association for Computational Linguistics (ACL, Findings), 2026. Suqin Yuan, Xingrui Yu, Jiyang Zheng, Lei Feng, Dadong Wang, Ivor Tsang, Tongliang Liu.
Mitigating Mismatch within Reference-based Preference Optimization.
In International Conference on Learning Representations (ICLR), 2026,
[PDF]. Zhenglin Wan*, Xingrui Yu*†, David Mark Bossens, Yueming Lyu, Qing Guo, Flint Xiaofeng Fan, Yew-Soon Ong, Ivor Tsang.
Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity.
In International Conference on Machine Learning (ICML), 2025. Heyang Zhao*, Xingrui Yu*, David Mark Bossens*, Ivor W. Tsang, Quanquan Gu.
Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration.
In International Conference on Learning Representations (ICLR), 2025,
[PDF]. Zhenglin Wan*, Anjun Gao*, Xingrui Yu, Pingfu Chao, Jun Song, Maohao Ran.
POI Recommendation via Multi-Objective Adversarial Imitation Learning.
In AAAI Conference on Artificial Intelligence (AAAI), 2025. Xingrui Yu*†, Zhenglin Wan*, David Mark Bossens, Yueming Lyu, Qing Guo, and Ivor W. Tsang.
Imitation from Diverse Behaviors: Wasserstein Quality Diversity Imitation Learning with Single-Step Archive Exploration.
In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2025,
[PDF]. Xingrui Yu, Bo Han, Ivor W. Tsang.
USN: A Robust Imitation Learning Method against Diverse Action Noise.
Journal of Artificial Intelligence Research (JAIR), 2024,
[PDF]. Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama.
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust.
In International Conference on Machine Learning (ICML), 2020,
[PDF]. Xingrui Yu, Yueming Lyu and Ivor W. Tsang.
Intrinsic Reward Driven Imitation Learning via Generative Model.
In International Conference on Machine Learning (ICML), 2020,
[PDF]
[Code]
[Slides]
[WebPage]. Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang and Masashi Sugiyama.
How does Disagreement Help Generalization Against Label Corruption?
In International Conference on Machine Learning (ICML), 2019,
[PDF]
[Code]. Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang and Masashi Sugiyama.
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels.
In Advances in Neural Information Processing Systems (NeurIPS), 2018,
[PDF]
[Code]. Xingrui Yu, He Zhang, Chunbo Luo, Hairong Qi and Peng Ren.
Oil Spill Segmentation via Adversarial f-divergence Learning.
IEEE Transactions on Geoscience and Remote Sensing (TGRS), 56(9): 4973-4988, 2018,
[PDF]
[Code].
Academic Service
Reviewer of ICML, ICLR, AAAI, IJCAI, ACML Reviewer of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Reviewer of IEEE Transactions on Geoscience and Remote Sensing (TGRS) Reviewer of IEEE Transactions on Machine Learning Research (TMLR) Reviewer of Journal of Artificial Intelligence Research (JAIR) Reviewer of Pattern Recognition (PR) Reviewer of Machine Learning (MLJ)
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