About Me
I am a Research Scientist at Google Cloud AI Research. I obtained my PhD from University of Southern California (USC), advised by Prof. Xiang Ren.
My research focuses on building trustworthy Natural Language Processing (NLP) systems. Specifically, I’m interested in alignment, safety, and robustness of Large Language Models (LLMs).
You can find my CV here.
Publications
(* indicates equal contribution)
Test-Time Backdoor Mitigation for Black-Box Large Language Models with Defensive Demonstrations
Wenjie Mo, Jiashu Xu, Qin Liu, Jiongxiao Wang, Jun Yan, Chaowei Xiao, Muhao Chen
Findings of NAACL 2025 [paper]
How Susceptible are Large Language Models to Ideological Manipulation?
Kai Chen, Zihao He, Jun Yan, Taiwei Shi, Kristina Lerman
EMNLP 2024 [paper] Best Paper Runner-up at SeT LLM @ ICLR 2024
Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection
Jun Yan, Vikas Yadav*, Shiyang Li*, Lichang Chen, Zheng Tang, Hai Wang, Vijay Srinivasan, Xiang Ren, Hongxia Jin
NAACL 2024 [paper] [project page]
Instruction-Following Evaluation through Verbalizer Manipulation
Shiyang Li, Jun Yan, Hai Wang, Zheng Tang, Xiang Ren, Vijay Srinivasan, Hongxia Jin
Findings of NAACL 2024 [paper]
AlpaGasus: Training A Better Alpaca with Fewer Data
Lichang Chen*, Shiyang Li*, Jun Yan, Hai Wang, Kalpa Gunaratna, Vikas Yadav, Zheng Tang, Vijay Srinivasan, Tianyi Zhou, Heng Huang, Hongxia Jin
ICLR 2024 [paper] [project page]
BITE: Textual Backdoor Attacks with Iterative Trigger Injection
On the Robustness of Reading Comprehension Models to Entity Renaming
RockNER: A Simple Method to Create Adversarial Examples for Evaluating the Robustness of Named Entity Recognition Models
AdaTag: Multi-Attribute Value Extraction from Product Profiles with Adaptive Decoding
Jun Yan, Nasser Zalmout, Yan Liang, Christan Grant, Xiang Ren, Xin Luna Dong
ACL 2021 [paper]
Learning Contextualized Knowledge Structures for Commonsense Reasoning
Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering
Learning from Explanations with Neural Execution Tree
Learning Dual Retrieval Module for Semi-Supervised Relation Extraction
Preprints
(* indicates equal contribution)
In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents
Zhen Tan, Jun Yan, I-Hung Hsu, Rujun Han, Zifeng Wang, Long T. Le, Yiwen Song, Yanfei Chen, Hamid Palangi, George Lee, Anand Iyer, Tianlong Chen, Huan Liu, Chen-Yu Lee, Tomas Pfister
arXiv:2503.08026 [paper]
Magnet: Multi-turn Tool-use Data Synthesis and Distillation via Graph Translation
Fan Yin, Zifeng Wang, I-Hung Hsu, Jun Yan, Ke Jiang, Yanfei Chen, Jindong Gu, Long T. Le, Kai-Wei Chang, Chen-Yu Lee, Hamid Palangi, Tomas Pfister
arXiv:2503.07826 [paper]
Rethinking Backdoor Detection Evaluation for Language Models
Jun Yan, Wenjie Mo, Xiang Ren, Robin Jia
arXiv:2409.00399 [paper]
GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks
Xinlu Zhang*, Yujie Lu*, Weizhi Wang*, An Yan, Jun Yan, Lianke Qin, Heng Wang, Xifeng Yan, William Yang Wang, Linda Ruth Petzold
arXiv:2311.01361 [paper]
Honors & Awards
- Sep 2019: My project receives support from Adobe Data Science Research Award ($50,000), PI: Prof. Xiang Ren
- Aug 2019: Annenberg Fellowship, University of Southern California
- Jul 2019: Excellent Graduate, Tsinghua University
- Oct 2018: Evergrande Scholarship, Tsinghua University
- Oct 2017: Samsung Scholarship, Tsinghua University
- Oct 2016: JJWorld Scholarship, Tsinghua University
Education
University of Southern California
Ph.D. in Computer Science
2019 - 2024 Los Angeles, CA, U.S.
Tsinghua University
B.Eng. in Electronic Engineering
2015 - 2019 Beijing, China