About

Hi there! I’m Baixiang, a CS PhD student at Emory University, advised by Dr. Kai Shu. My research has focused on improving the factuality, safety, and robustness of foundation models, particularly through model editing, a technique that enables precise and efficient modifications to large language models while preserving their overall capabilities.

Previously, I have worked on authorship attribution, which aims to identify the author of a text based on their unique writing style.

In my free time, I enjoy spending time in nature and staying active through various outdoor sports. Iโ€™m an avid runner and swimmer, and Iโ€™ve recently taken up weightlifting. I also find joy in playing the piano and expanding my reading list.

[LinkedIn] [Google Scholar] [GitHub] [Email] [Twitter]

Publications and Preprints

Model Editing as a Double-Edged Sword: Steering Agent Ethical Behavior Toward Beneficence or Harm
Baixiang Huang, Zhen Tan, Haoran Wang, Zijie Liu, Dawei Li, Ali Payani, Huan Liu, Tianlong Chen, Kai Shu.
AAAI 2026 Oral [arXiv] [GitHub] [Website]

Can Editing LLMs Inject Harm?
Canyu Chen*, Baixiang Huang*, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Wang, Philip Torr, Dawn Song, Kai Shu.
AAAI 2026 [arXiv] [GitHub] [Website]

Can Knowledge Editing Really Correct Hallucinations?
Baixiang Huang, Canyu Chen, Xiongxiao Xu, Ali Payani, Kai Shu.
ICLR 2025 [arXiv] [GitHub] [Website]

SST: Multi-Scale Hybrid Mamba-Transformer Experts for Long-Short Range Time Series Forecasting
Xiongxiao Xu, Canyu Chen, Yueqing Liang, Baixiang Huang, Guangji Bai, Liang Zhao, Kai Shu.
CIKM 2025 [arXiv] [GitHub]

Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges
Baixiang Huang, Canyu Chen, Kai Shu.
ACM SIGKDD Exploration 2024 [arXiv] [Paper List] [Website]

Can Large Language Models Identify Authorship?
Baixiang Huang, Canyu Chen, Kai Shu. 
EMNLP 2024 Findings [arXiv] [GitHub]

TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks
Baixiang Huang, Bryan Hooi, Kai Shu. 
ACM SIGSPATIAL 2023 [arXiv] [GitHub]


Preprints

Towards Effective Model Editing for LLM Personalization
Baixiang Huang, Limeng Cui, Jiapeng Liu, Haoran Wang, Jiawei Xu, Zhuiyue Tan, Yutong Chen, Chen Luo, Yi Liu, Kai Shu.
arXiv preprint (2025) [arXiv] [GitHub] [Website]

Who's Your Judge? On the Detectability of LLM-Generated Judgments
Dawei Li, Zhen Tan, Chengshuai Zhao, Bohan Jiang, Baixiang Huang, Pingchuan Ma, Abdullah Alnaibari, Kai Shu, Huan Liu.
arXiv preprint (2025) [arXiv] [GitHub] [Website]

Privacy-Aware Decoding: Mitigating Privacy Leakage of Large Language Models in Retrieval-Augmented Generation
Haoran Wang, Xiongxiao Xu, Baixiang Huang, Kai Shu.
arXiv preprint (2025) [arXiv] [GitHub]

* Equal Contribution

Tools and Resources

BibTeX to Markdown Converter: Convert BibTeX files into clean Markdown paper lists with PDF links

One-Click Google Scholar BibTeX: Chrome extension to instantly copy BibTeX citations from Google Scholar with a single click

Medium Blog

How to Visualize Street Networks

Can Editing LLMs Inject Harm? A Deep Dive into New Safety Threats

Authorship Attribution: Why Identifying Who Wrote What is More Important Than Ever in the Age of LLMs