| Graph neural networks: A review of methods and applications J Zhou, G Cui, S Hu, Z Zhang, C Yang, Z Liu, L Wang, C Li, M Sun AI open 1, 57-81, 2020 | 5244 | 2020 |
| Adaptive graph encoder for attributed graph embedding G Cui, J Zhou, C Yang, Z Liu Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 190 | 2020 |
| Tool learning with foundation models Y Qin, S Hu, Y Lin, W Chen, N Ding, G Cui, Z Zeng, Y Huang, C Xiao, ... arXiv preprint arXiv:2304.08354, 2023 | 155 | 2023 |
| Introduction to graph neural networks Z Liu, J Zhou Springer Nature, 2022 | 129 | 2022 |
| Full-scale information diffusion prediction with reinforced recurrent networks C Yang, H Wang, J Tang, C Shi, M Sun, G Cui, Z Liu IEEE Transactions on Neural Networks and Learning Systems 34 (5), 2271-2283, 2021 | 104 | 2021 |
| Prototypical verbalizer for prompt-based few-shot tuning G Cui, S Hu, N Ding, L Huang, Z Liu ACL, 2022 | 73 | 2022 |
| Exploring the universal vulnerability of prompt-based learning paradigm L Xu, Y Chen, G Cui, H Gao, Z Liu arXiv preprint arXiv:2204.05239, 2022 | 54 | 2022 |
| Ultrafeedback: Boosting language models with high-quality feedback G Cui, L Yuan, N Ding, G Yao, W Zhu, Y Ni, G Xie, Z Liu, M Sun arXiv preprint arXiv:2310.01377, 2023 | 49 | 2023 |
| A unified evaluation of textual backdoor learning: Frameworks and benchmarks G Cui, L Yuan, B He, Y Chen, Z Liu, M Sun NeurIPS 2022 Datasets and Benchmarks Track, 2022 | 41 | 2022 |
| A close look into the calibration of pre-trained language models Y Chen, L Yuan, G Cui, Z Liu, H Ji arXiv preprint arXiv:2211.00151, 2022 | 31 | 2022 |
| Why should adversarial perturbations be imperceptible? rethink the research paradigm in adversarial NLP Y Chen, H Gao, G Cui, F Qi, L Huang, Z Liu, M Sun arXiv preprint arXiv:2210.10683, 2022 | 19 | 2022 |
| Revisiting Out-of-distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations L Yuan, Y Chen, G Cui, H Gao, F Zou, X Cheng, H Ji, Z Liu, M Sun Advances in Neural Information Processing Systems 36, 2024 | 16 | 2024 |
| Moderate-fitting as a natural backdoor defender for pre-trained language models B Zhu, Y Qin, G Cui, Y Chen, W Zhao, C Fu, Y Deng, Z Liu, J Wang, W Wu, ... Advances in Neural Information Processing Systems 35, 1086-1099, 2022 | 12 | 2022 |
| Machine-learning-driven matrix ordering for power grid analysis G Cui, W Yu, X Li, Z Zeng, B Gu 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE), 984-987, 2019 | 12 | 2019 |
| Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback T Yu, Y Yao, H Zhang, T He, Y Han, G Cui, J Hu, Z Liu, HT Zheng, M Sun, ... arXiv preprint arXiv:2312.00849, 2023 | 10 | 2023 |
| From adversarial arms race to model-centric evaluation: Motivating a unified automatic robustness evaluation framework Y Chen, H Gao, G Cui, L Yuan, D Kong, H Wu, N Shi, B Yuan, L Huang, ... arXiv preprint arXiv:2305.18503, 2023 | 4 | 2023 |
| Decoder Tuning: Efficient Language Understanding as Decoding G Cui, W Li, N Ding, L Huang, Z Liu, M Sun ACL, 2022 | 4 | 2022 |
| Few-shot classification with hypersphere modeling of prototypes N Ding, Y Chen, G Cui, X Wang, HT Zheng, Z Liu, P Xie arXiv preprint arXiv:2211.05319, 2022 | 4 | 2022 |
| Evaluating modules in graph contrastive learning G Cui, Y Du, C Yang, J Zhou, L Xu, X Zhou, X Cheng, Z Liu arXiv preprint arXiv:2106.08171, 2021 | 3 | 2021 |
| Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment Y Guo, G Cui, L Yuan, N Ding, J Wang, H Chen, B Sun, R Xie, J Zhou, ... arXiv preprint arXiv:2402.19085, 2024 | 2 | 2024 |
Zhiyuan LiuAssociate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
