About Me
I am a Research Scientist at Google. I obtained my PhD from University of Southern California (USC), advised by Prof. Xiang Ren.
I work on improving agentic capability and trustworthiness of Large Language Models (LLMs).
You can find my CV here.
Publications and Preprints
(* indicates equal contribution)
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gemini Team, Google
Technical Report, 2025 [paper]
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
ACL 2025 [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
ACL 2025 [paper]
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
Rethinking Backdoor Detection Evaluation for Language Models
Jun Yan, Wenjie Mo, Xiang Ren, Robin Jia
arXiv:2409.00399 [paper]
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]
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]
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
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