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About Me
I am a Ph.D. student in Statistics at University of Georgia from 08/2024 to 06/2028. Before that, I received my Bachelor's degree in Computer Science from Nankai University in China. My current research interest is explainable LLM and trustworthy machine learning.
Publication
- X Gong, S Yang, Z Cao, L Billard, D Wang. Faithful-Patchscopes: Understanding and Mitigating Model Bias in Hidden Representations Explanation of Large Language Models.
- X Gong, Y Chen, S Wu, F Wang, P Ma, W Zhong. S2MNet: Speckle-To-Mesh Net for Three-Dimensional Cardiac Morphology Reconstruction via Echocardiogram.
- S Wu, X Gong, Y Chen, Y Liu, W Zhong, P Ma. Fisher Contrastive Learning: A Robust Solution to the Feature Suppression Effect
- J Hu, S Yang, X Gong, H Wang, W Liu, D Wang. MONICA: Real-Time Monitoring and Calibration of Chain-of-Thought Sycophancy in Large Reasoning Models.
- Z Zhang, T Wang, X Gong, Y Shi, H Wang, D Wang, L Hu. When modalities conflict: How unimodal reasoning uncertainty governs preference dynamics in mllms.
- S Yang, J Wu, X Gong, X Wu, D Wong, N Liu, D Wang. Investigating CoT Monitorability in Large Reasoning Models.
- L Hu, T Huang, H Xie, X Gong, C Ren, Z Hu, L Yu, P Ma, D Wang. Semi-supervised concept bottleneck models. International Conference on Computer Vision 2025
- S Wu, B Yang, H Yang, S Coshatt, X Gong, R Parasuraman, J Conrad, W Zhong, J Ye, P Ma, W Song. Online Adaptively Anomaly Detection in Networked Electrical Machines by Enveloped Singular Spectrum Transformation. IEEE Internet of Things Journal 2024
- L Fang, X Yu, J Cai, Y Chen, S Wu, Z Liu, Z Yang, H Lu, **X Gong…**etc. Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions. Artificial Intelligence Review 2026
Teaching
Teaching Assistant
- Statistical Inference for Data Scientists; Mathematical Statistics; Introduction to Probability for Life Sciences, Spring 2026
- Applied Regression Analysis, UGA, Summer 2025