Junjie Wu 伍君杰

👋 Hi!

I am a final-year Ph.D. candidate at The Hong Kong University of Science and Technology (HKUST), supervised by Prof. Dit-Yan Yeung.

Previously, I was a Research Scientist Intern at GenAI, Meta, working with Kaitai Zhang, Xuan Kan, Zihao He, and Shunwen Tan. Before that, I was a visiting Ph.D. student at Yale University, advised by Prof. Arman Cohan. During my Ph.D. study, I have also been fortunate to collaborate closely with Mo Yu and Lemao Liu at WeChat AI and Tencent AI Lab, Tencent.

Email / Google Scholar / LinkedIn / CV
Junjie Wu

News

Research

My current research interests lie in building more intelligent and reliable large (language/vision) models.

Specifically, here are some topics I currently focus on:

Education / Experience

  • 2020/09 - Present: Ph.D. Candidate at HKUST
  • 2025/06 - 2026/01: Research Scientist Intern at GenAI, Meta
  • 2024/09 - 2025/02: Visiting Ph.D. Student at Yale NLP, Yale University
  • 2024/05 - 2025/05: Research Intern at WeChat AI, Tencent
  • 2021/06 - 2024/01: Research Intern at NLP Group, Tencent AI Lab
  • 2016/09 - 2020/06: B.S. in Statistics, Sun Yat-sen University (GPA: 3.8/4.0)
  • 2019/07 - 2019/10: Visiting Student at the University of Michigan, Ann Arbor

Publications (* Equal contribution)

Preprints
Mindscape-Aware Retrieval Augmented Generation for Improved Long Context Understanding
Yuqing Li, Jiangnan Li, Zheng Lin, Ziyan Zhou, Junjie Wu, Weiping Wang, Jie Zhou, and Mo Yu
[Paper]
SitEmb-v1.5: Improved Context-Aware Dense Retrieval for Semantic Association and Long Story Comprehension
Junjie Wu, Jiangnan Li, Yuqing Li, Lemao Liu, Liyan Xu, Jiwei Li, Dit-Yan Yeung, Jie Zhou, and Mo Yu
[Paper] [Model]
SCAT: Robust Self-supervised Contrastive Learning via Adversarial Training for Text Classification
Junjie Wu and Dit-Yan Yeung
[Paper]
Accepted
Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models
Junjie Wu*, Gefei Gu*, Yanan Zheng, Dit-Yan Yeung, and Arman Cohan
ACL 2025
[Paper] [Project] [Code]
Understanding LLMs' Fluid Intelligence Deficiency: An Analysis of the ARC Task
Junjie Wu, Mo Yu, Lemao Liu, Dit-Yan Yeung, and Jie Zhou
NAACL 2025 (Oral)
[Paper] [Project] [Code]
The Stochastic Parrot on LLM’s Shoulder: A Summative Assessment of Physical Concept Understanding
Mo Yu*, Lemao Liu*, Junjie Wu*, Tsz Ting Chung*, Shunchi Zhang*, Jiangnan Li, Dit-Yan Yeung, and Jie Zhou
NAACL 2025 (Oral)
[Paper] [Project] [Code]
Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models
Junjie Wu*, Tsz Ting Chung*, Kai Chen*, and Dit-Yan Yeung
TMLR 2025
[Paper] [Project] [Code]
Rethinking Targeted Adversarial Attacks for Neural Machine Translation
Junjie Wu, Lemao Liu, Wei Bi, and Dit-Yan Yeung
ICASSP 2024
[Paper] [Code]
Towards General Error Diagnosis via Behavioral Testing in Machine Translation
Junjie Wu, Lemao Liu, and Dit-Yan Yeung
EMNLP 2023 (Presented at the GenBench Workshop @EMNLP 2023)
[Paper] [Code]
Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations
Jiajun Bao*, Junjie Wu*, Yiming Zhang*, Eshwar Chandrasekharan, and David Jurgens
The Web Conference 2021
[Paper] [Code]
Augmenting Topic-Aware Knowledge-Grounded Conversations with Dynamic Built Knowledge Graphs
Junjie Wu and Hao Zhou
DeeLIO Workshop @ NAACL 2021
[Paper]