Gaojie Jin

According to our database, Gaojie Jin authored at least 27 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Shapley Uncertainty in Natural Language Generation.

Meilin Zhu, Gaojie Jin, Xiaowei Huang, Lijun Zhang

CoRR, July, 2025

ThermoRL:Structure-Aware Reinforcement Learning for Protein Mutation Design to Enhance Thermostability.

Xiangwen Wang, Gaojie Jin, Xiaowei Huang, Ronghui Mu

CoRR, July, 2025

Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers.

Gaojie Jin, Tianjin Huang, Ronghui Mu, Xiaowei Huang

CoRR, March, 2025

Stable-SPAM: How to Train in 4-Bit More Stably than 16-Bit Adam.

Tianjin Huang, Haotian Hu, Zhenyu Zhang, Gaojie Jin, Xiang Li, Li Shen, Tianlong Chen, Lu Liu, Qingsong Wen, Zhangyang Wang, Shiwei Liu

CoRR, February, 2025

Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing.

Sihao Wu, Xiaonan Si, Chi Xing, Jianhong Wang, Gaojie Jin, Guangliang Cheng, Lijun Zhang, Xiaowei Huang

CoRR, February, 2025

Toward Linearly Regularizing the Geometric Bottleneck of Linear Generalized Attention.

Jiaxu Liu, Xinping Yi, Xiangyu Yin, Yuhang Song, Gaojie Jin, Xiaowei Huang

Trans. Mach. Learn. Res., 2025

Invariant Correlation of Representation With Label.

Gaojie Jin, Ronghui Mu, Xinping Yi, Xiaowei Huang, Lijun Zhang

IEEE Trans. Inf. Forensics Secur., 2025

Enhancing Robust Fairness via Confusional Spectral Regularization.

Gaojie Jin, Sihao Wu, Jiaxu Liu, Tianjin Huang, Ronghui Mu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training.

Tianjin Huang, Ziquan Zhu, Gaojie Jin, Lu Liu, Zhangyang Wang, Shiwei Liu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

A survey of safety and trustworthiness of large language models through the lens of verification and validation.

Xiaowei Huang, Wenjie Ruan, Wei Huang, Gaojie Jin, Yi Dong, Changshun Wu, Saddek Bensalem, Ronghui Mu, Yi Qi, Xingyu Zhao, Kaiwen Cai, Yanghao Zhang, Sihao Wu, Peipei Xu, Dengyu Wu, André Freitas, Mustafa A. Mustafa

Artif. Intell. Rev., July, 2024

Formal verification of robustness and resilience of learning-enabled state estimation systems.

Wei Huang, Yifan Zhou, Gaojie Jin, Youcheng Sun, Jie Meng, Fan Zhang, Xiaowei Huang

Neurocomputing, 2024

Safeguarding Large Language Models: A Survey.

Yi Dong, Ronghui Mu, Yanghao Zhang, Siqi Sun, Tianle Zhang, Changshun Wu, Gaojie Jin, Yi Qi, Jinwei Hu, Jie Meng, Saddek Bensalem, Xiaowei Huang

CoRR, 2024

Direct Training Needs Regularisation: Anytime Optimal Inference Spiking Neural Network.

Dengyu Wu, Yi Qi, Kaiwen Cai, Gaojie Jin, Xinping Yi, Xiaowei Huang

CoRR, 2024

Building Guardrails for Large Language Models.

Yi Dong, Ronghui Mu, Gaojie Jin, Yi Qi, Jinwei Hu, Xingyu Zhao, Jie Meng, Wenjie Ruan, Xiaowei Huang

CoRR, 2024

Class-Aware Cross Pseudo Supervision Framework for Semi-Supervised Multi-organ Segmentation in Abdominal CT Scans.

Deqian Yang, Haochen Zhao, Gaojie Jin, Hui Meng, Lijun Zhang

Proceedings of the Pattern Recognition and Computer Vision - 7th Chinese Conference, 2024

Position: Building Guardrails for Large Language Models Requires Systematic Design.

Yi Dong, Ronghui Mu, Gaojie Jin, Yi Qi, Jinwei Hu, Xingyu Zhao, Jie Meng, Wenjie Ruan, Xiaowei Huang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors.

Tao Lin, Lijia Yu, Gaojie Jin, Renjue Li, Peng Wu, Lijun Zhang

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Machine Learning Safety

Xiaowei Huang, Gaojie Jin, Wenjie Ruan

Artificial Intelligence: Foundations, Theory, and Algorithms, Springer, ISBN: 978-981-19-6813-6, 2023

Optimising Event-Driven Spiking Neural Network with Regularisation and Cutoff.

Dengyu Wu, Gaojie Jin, Han Yu, Xinping Yi, Xiaowei Huang

CoRR, 2023

TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models.

Liang Zhang, Nathaniel Xu, Pengfei Yang, Gaojie Jin, Cheng-Chao Huang, Lijun Zhang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability.

Wei Huang, Xingyu Zhao, Gaojie Jin, Xiaowei Huang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Randomized Adversarial Training via Taylor Expansion.

Gaojie Jin, Xinping Yi, Dengyu Wu, Ronghui Mu, Xiaowei Huang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Certified Policy Smoothing for Cooperative Multi-Agent Reinforcement Learning.

Ronghui Mu, Wenjie Ruan, Leandro Soriano Marcolino, Gaojie Jin, Qiang Ni

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Weight Expansion: A New Perspective on Dropout and Generalization.

Gaojie Jin, Xinping Yi, Pengfei Yang, Lijun Zhang, Sven Schewe, Xiaowei Huang

Trans. Mach. Learn. Res., 2022

Neuronal Correlation: a Central Concept in Neural Network.

Gaojie Jin, Xinping Yi, Xiaowei Huang

CoRR, 2022

Enhancing Adversarial Training with Second-Order Statistics of Weights.

Gaojie Jin, Xinping Yi, Wei Huang, Sven Schewe, Xiaowei Huang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2020

How does Weight Correlation Affect Generalisation Ability of Deep Neural Networks?

Gaojie Jin, Xinping Yi, Liang Zhang, Lijun Zhang, Sven Schewe, Xiaowei Huang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020