Ganqu Cui
Ph.D
Room 4-506, FIT Building
Dept. of Computer Science and Technology
Tsinghua University
Beijing, China, 100084.
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Biography
I am a researcher in Shanghai AI Laboratory. I obtained my Ph.D degree from THUNLP Lab, Dept. of Computer Science and Technology, Tsinghua University, advised by Prof. Zhiyuan Liu.
Before that, I obtained my B.S. degree of Mathematics and Physics, Tsinghua University in July 2019.
My research interests lie at LLM alignment. Previously, I did some research on representation learning on graphs, especially graph neural networks and their application.
News
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[07/2024] I joined Shanghai AI Laboratory as a research scientist.
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[07/2024] I graduated from Tsinghua with Tsinghua Outstanding Doctoral Dissertation award.
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[05/2024] UltraFeedback was accepted by ICML 2024.
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[04/2024] Checkout Eurus.
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[09/2023] Checkout UltraFeedback.
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[09/2023] One paper was accepted by NeurIPS 2023.
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[05/2023] Four papers were accepted by ACL 2023 (2 Findings).
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[04/2023] Checkout our Tool Learning paper.
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[10/2022] One paper was accepted by EMNLP 2022.
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[09/2022] Two papers were accepted by NeurIPS 2022 (1 Spotlight).
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[05/2022] One paper was accepted by NAACL 2022 Findings.
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[03/2022] One paper was accepted by ACL 2022.
* indicates equal contribution.
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Advancing LLM Reasoning Generalists with Preference Trees
Lifan Yuan*, Ganqu Cui*, Hanbin Wang*, Ning Ding, Xingyao Wang, Jia Deng, Boji Shan, Huimin Chen, Ruobing Xie, Yankai Lin, Zhenghao Liu, Bowen Zhou, Hao Peng, Zhiyuan Liu, Maosong Sun.
Preprint
[code]
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UltraFeedback: Boosting Language Models with Scaled AI Feedback
Ganqu Cui*, Lifan Yuan*, Ning Ding, Guanming Yao, Bingxiang He, Wei Zhu, Yuan Ni, Guotong Xie, Ruobing Xie, Yankai Lin, Zhiyuan Liu, Maosong Sun.
ICML 2024
[code]
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Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis, and LLMs Evaluations
Lifan Yuan, Yangyi Chen, Ganqu Cui, Hongcheng Gao, Fangyuan Zou, Xingyi Cheng, Heng Ji, Zhiyuan Liu, Maosong Sun.
NeurIPS Datasets & Benchmarks 2022
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Removing Backdoors in Pre-trained Models by Regularized Continual Pre-training
Biru Zhu*, Ganqu Cui*, Yangyi Chen, Yujia Qin, Lifan Yuan, Chong Fu, Yangdong Deng, Zhiyuan Liu, Maosong Sun, Ming Gu.
TACL
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Tool Learning with Foundation Models
Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding, Ganqu Cui, Zheni Zeng, Yufei Huang, Chaojun Xiao, Chi Han, Yi Ren Fung, Yusheng Su, Huadong Wang, Cheng Qian, Runchu Tian, Kunlun Zhu, Shihao Liang, Xingyu Shen, Bokai Xu, Zhen Zhang, Yining Ye, Bowen Li, Ziwei Tang, Jing Yi, Yuzhang Zhu, Zhenning Dai, Lan Yan, Xin Cong, Yaxi Lu, Weilin Zhao, Yuxiang Huang, Junxi Yan, Xu Han, Xian Sun, Dahai Li, Jason Phang, Cheng Yang, Tongshuang Wu, Heng Ji, Zhiyuan Liu, Maosong Sun.
Preprint
[code]
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Decoder Tuning: Efficient Language Understanding as Decoding
Ganqu Cui, Wentao Li, Ning Ding, Longtao Huang, Zhiyuan Liu, Maosong Sun.
ACL 2023
[code]
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A Close Look into the Calibration of Pre-trained Language Models
Yangyi Chen*, Lifan Yuan*, Ganqu Cui, Zhiyuan Liu, Heng Ji.
ACL 2023
[code]
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From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework
Yangyi Chen*, Hongcheng Gao*, Ganqu Cui*, Lifan Yuan, Dehan Kong, Hanlu Wu, Ning Shi, Bo Yuan, Longtao Huang, Hui Xue, Zhiyuan Liu, Maosong Sun, Heng Ji.
Findings of ACL 2023
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Few-shot Classification with Hypersphere Modeling of Prototypes
Ning Ding, Yulin Chen, Ganqu Cui, Xiaobin Wang, Hai-Tao Zheng, Zhiyuan Liu, Pengjun Xie
Findings of ACL 2023
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Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP
Yangyi Chen, Hongcheng Gao, Ganqu Cui, Fanchao Qi, Longtao Huang, Zhiyuan Liu, Maosong Sun.
EMNLP 2022
[code]
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A Unified Evaluation of Textual Backdoor Learning: Frameworks and Benchmarks (Spotlight)
Ganqu Cui*, Lifan Yuan*, Bingxiang, He, Yangyi Chen, Zhiyuan Liu, Maosong Sun.
NeurIPS Datasets & Benchmarks 2022
[code]
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Moderate-fitting as a Natural Backdoor Defender for Pre-trained Language Models
Biru Zhu, Yujia Qin, Ganqu Cui, Yangyi Chen, Weilin Zhao, Chong Fu, Yangdong Deng, Zhiyuan Liu, Jingang Wang, Wei Wu, Maosong Sun, Ming Gu.
NeurIPS 2022
[code]
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Exploring the Universal Vulnerability of Prompt-based Learning Paradigm
Lei Xu, Yangyi Chen, Ganqu Cui, Hongcheng Gao, Zhiyuan Liu
Findings of NAACL 2022
[code]
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Prototypical Verbalizer for Prompt-based Few-shot Tuning
Ganqu Cui, Shengding Hu, Ning Ding, Longtao Huang, Zhiyuan Liu.
ACL 2022
[code]
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Evaluating Modules in Graph Contrastive Learning
Ganqu Cui, Yufeng Du, Cheng Yang, Jie Zhou, Liang Xu, Lifeng Wang, Zhiyuan Liu.
Preprint
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Graph Neural Networks: A Review of Methods and Applications
Jie Zhou*, Ganqu Cui*, Shengding Hu, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li, Maosong Sun.
AI Open 2021
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Adaptive Graph Encoder for Attributed Graph Embedding
Ganqu Cui, Jie Zhou, Cheng Yang, Zhiyuan Liu.
KDD 2020
[code]
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Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks
Cheng Yang, Jian Tang, Maosong Sun, Ganqu Cui, Zhiyuan Liu.
IJCAI 2019
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Machine-Learning-Driven Matrix Ordering for Power Grid Analysis
Ganqu Cui, Wenjian Yu, Xin Li, Zhiyu Zeng, Ben Gu.
DATE 2019
Honors & Awards
清华大学优秀博士论文 (Top 10%) |
清华大学优秀毕业生 (Top 4%) |
龙湖奖学金, 2022, 2023 |
清华之友-搜狐研发奖学金, 2022 |
清华之友-唐君远奖学金, 2023 |
Projects
Professional Activities
Conference Reviews:
The Web Conference 2021
EMNLP 2022
NeurIPS 2022
ACL 2023
SIGIR 2023
Journal Reviews:
IEEE Transactions on Knowledge and Data Engineering (TKDE)
AI Open
Teaching Assistant
2019-2023 | Spring | TA in Natural Language Processing |
2022-2023 | Fall | TA in Writing and Communication |