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Jiaxu Zhao
Jiaxu Zhao
Eindhoven University of Technology
Bestätigte E-Mail-Adresse bei tue.nl
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Zitiert von
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You can have better graph neural networks by not training weights at all: Finding untrained gnns tickets
T Huang, T Chen, M Fang, V Menkovski, J Zhao, L Yin, Y Pei, DC Mocanu, ...
arXiv preprint arXiv:2211.15335, 2022
222022
CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models
J Zhao, M Fang, Z Shi, Y Li, L Chen, M Pechenizkiy
In Proceedings of the 61st Annual Meeting of the Association for …, 2023
212023
Gptbias: A comprehensive framework for evaluating bias in large language models
J Zhao, M Fang, S Pan, W Yin, M Pechenizkiy
arXiv preprint arXiv:2312.06315, 2023
162023
Synergizing Foundation Models and Federated Learning: A Survey
S Li, F Ye, M Fang, J Zhao, YH Chan, ECH Ngai, T Voigt
arXiv preprint arXiv:2406.12844, 2024
32024
REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training
J Zhao, L Yin, S Liu, M Fang, M Pechenizkiy
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023
22023
CHAmbi: A New Benchmark on Chinese Ambiguity Challenges for Large Language Models
Q Zhang, S Cai, J Zhao, M Pechenizkiy, M Fang
Findings of the Association for Computational Linguistics: EMNLP 2024, 14883 …, 2024
12024
You can have better graph neural networks by not training weights at all: Finding untrained graph tickets
T Huang, T Chen, M Fang, V Menkovski, J Zhao, L Yin, Y Pei, DC Mocanu, ...
1st Learning on Graphs Conference, LOG 2022, 2022
12022
On Adversarial Robustness of Language Models in Transfer Learning
B Turbal, A Mazur, J Zhao, M Pechenizkiy
arXiv preprint arXiv:2501.00066, 2024
2024
More than Minorities and Majorities: Understanding Multilateral Bias in Language Generation
J Zhao, Z Shi, Y Li, Y Pei, L Chen, M Fang, M Pechenizkiy
Findings of the Association for Computational Linguistics ACL 2024, 9987-10001, 2024
2024
Twin-GAN for Neural Machine Translation.
J Zhao, L Huang, R Sun, L Bing, H Qu
ICAART (2), 87-96, 2021
2021
Assessing Vulnerabilities of Large Language Models to Social Bias Attacks
J Zhao, M Fang, F Ye, K Xu, Q Zhang, JT Zhou, M Pechenizkiy
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