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Ganqu Cui
Ganqu Cui
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Zitiert von
Zitiert von
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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
51302020
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
1872020
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
1522023
Introduction to graph neural networks
Z Liu, J Zhou
Springer Nature, 2022
1262022
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
1022021
Prototypical verbalizer for prompt-based few-shot tuning
G Cui, S Hu, N Ding, L Huang, Z Liu
ACL, 2022
712022
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
502022
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
452023
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
362022
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
292022
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
192022
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
152024
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
122019
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
112022
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
102023
Decoder Tuning: Efficient Language Understanding as Decoding
G Cui, W Li, N Ding, L Huang, Z Liu, M Sun
ACL, 2022
52022
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
42023
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
32022
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
32021
Capacitance extraction and power grid analysis using statistical and AI methods
W Yu, M Yang, Y Feng, G Cui, B Gu
2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC), 428-433, 2020
22020
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