Liu, Tongliang

Expressive power of parametrized quantum circuits

Du, Y., Hsieh, M.-H., Liu, T., & Tao, D. (2020) · Physical Review Research

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 318

Improving Medical Images Classification With Label Noise Using Dual-Uncertainty Estimation

Ju, L., Wang, X., Wang, L., Mahapatra, D., Zhao, X., Zhou, Q., Liu, T., & Ge, Z. (2022) · IEEE Transactions on Medical Imaging

Machine Learning and Data ClassificationArtificial Intelligence in Healthcare and Education

Cited by 128

A Second-Order Approach to Learning with Instance-Dependent Label Noise

Zhu, Z., Liu, T., & Liu, Y. (2020) · arXiv

Machine Learning and Data ClassificationDomain Adaptation and Few-Shot Learning

Cited by 100

Confidence Scores Make Instance-dependent Label-noise Learning Possible

Berthon, A., Han, B., Niu, G., Liu, T., & Sugiyama, M. (2020) · arXiv

Machine Learning and Data ClassificationMachine Learning and Algorithms

Cited by 57

DeepInception: Hypnotize Large Language Model to Be Jailbreaker

Li, X., Zhou, Z., Zhu, J., Yao, J., Liu, T., & Han, B. (2023) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 20

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Liu, B., Li, X., Zhang, J., Wang, J., He, T., Hong, S., Liu, H., Zhang, S., Song, K., Zhu, K., et al. (2025) · arXiv

Psychiatry, Mental Health, NeuroscienceArtificial Intelligence Applications

Cited by 16

AgentAuditor: Human-Level Safety and Security Evaluation for LLM Agents

Luo, H., Dai, S., Ni, C., Li, X., Zhang, G., Wang, K., Liu, T., & Salam, H. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 1

Flow: Modularized Agentic Workflow Automation

Niu, B., Song, Y., Lian, K., Shen, Y., Yao, Y., Zhang, K., & Liu, T. (2025) · arXiv

AI-based Problem Solving and PlanningMulti-Agent Systems and Negotiation

Cited by 1