Jun Yan

Research Scientist

Google

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

Jun Yan, Vansh Gupta, Xiang Ren

ACL 2023 [paper][code]

On the Robustness of Reading Comprehension Models to Entity Renaming

Jun Yan, Yang Xiao, Sagnik Mukherjee, Bill Yuchen Lin, Robin Jia, Xiang Ren

NAACL 2022 [paper][code]

RockNER: A Simple Method to Create Adversarial Examples for Evaluating the Robustness of Named Entity Recognition Models

Bill Yuchen Lin, Wenyang Gao, Jun Yan, Ryan Moreno, Xiang Ren

EMNLP 2021 [paper][code]

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

Jun Yan, Mrigank Raman, Aaron Chan, Tianyu Zhang, Ryan Rossi, Handong Zhao, Sungchul Kim, Nedim Lipka

Findings of ACL 2021 [paper][code]

Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering

Yanlin Feng*, Xinyue Chen*, Bill Yuchen Lin, Peifeng Wang, Jun Yan, Xiang Ren

EMNLP 2020 [paper][code]

Learning from Explanations with Neural Execution Tree

Ziqi Wang*, Yujia Qin*, Wenxuan Zhou, Jun Yan, Qinyuan Ye, Leonardo Neves, Zhiyuan Liu, Xiang Ren

ICLR 2020 [paper][code]

Learning Dual Retrieval Module for Semi-Supervised Relation Extraction

Hongtao Lin, Jun Yan, Meng Qu, Xiang Ren

TheWebConf 2019 [paper][code]

Language Modeling with Sparse Product of Sememe Experts

Yihong Gu*, Jun Yan*, Hao Zhu*, Zhiyuan Liu, Ruobing Xie, Maosong Sun, Fen Lin, Leyu Lin

EMNLP 2018 [paper][code]

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