About Me
I am an NLP engineer at WeChat AI, Tencent Inc.
I received my MS degree from the Department of Automation at Tsinghua University, supervised by Prof. Rui Jiang.
Previously, I finished my bachelor’s degree in Beijing Normal University, majoring in Computer Science and Technology.
My research interests fall in Natural Language Processing.
Education
![]() | Tsinghua University Sep. 2020 - Jun. 2023 Department of Automation Master in Control Science and Engineering Advisor: Rui Jiang | |
![]() | Beijing Normal University Sept. 2016 - Jun. 2020 College of Information Science and Technology Bachelor in Computer Science and Technology | |
![]() | University of Oxford Jul. 2017 - Aug. 2017 Oriel College Exchange Student |
Publications & Preprints
One-stop Training of Multiple Capacity Models.[Paper]
Lan Jiang, Haoyang Huang, Dongdong Zhang, Rui Jiang, Furu Wei
Preprint.
ROSE: Robust Selective Fine-tuning for Pre-trained Language Models. [Paper] [Code]
Lan Jiang, Hao Zhou, Yankai Lin, Peng Li, Jie Zhou, Rui Jiang.
EMNLP 2022.
On Length Divergence Bias in Textual Matching Models. [Paper] [Code]
Lan Jiang, Tianshu Lyu, Yankai Lin, Meng Chong, Xiaoyong Lyu, Dawei Yin.
Findings of ACL 2022.
Exploration of the Change Trend Analysis of the Epidemiological History of COVID-19 Patients Based on Natural Language Processing. [Paper]
Xiaolu Fei, Lan Jiang, Pengyu Chen, Jia Li, Lan Wei, Rui Jiang, Hairong Lv.
China Digital Medicine 2020 (Journal).
MAssistant: A Personal Knowledge Assistant for MOOC Learners. The Conference on Empirical Methods in Natural Language Processing. [Paper]
Lan Jiang, Shuhan Hu, Mingyu Huang, Zhichun Wang, Jinjian Yang, Xiaoju Ye, Wei Zheng.
EMNLP 2019.
Experiences
- Research Intern advised by Haoyang Huang
- Study the topic on Mixture of Experts (MoE).
- Research Intern advised by Hao Zhou and Yankan Lin
- Study the topic on the robustness of pre-trained language model
- Algorithm Intern advised by Ruijie Zhang and Min Zeng
- Study the topic on topic-controlled dialogue generation
- Research Intern advised by Tianshu Lyu
- Study the topic on the length divergence bias of textual matching models
Honors & Awards
Teaching Assistantship
Leadership
Lead four departments with more than 50 staff members. Organize several events with over 100 participants
Awarded the 2017 Beijing Excellent Class