@article{wenhui2026,
title = {CE-GAD: Curriculum-Efficient On-Policy Adversarial Distillation of Large Language Models},
author = {Zhu, Wenhui and Sang, Hejian and Chen, Xiwen and Wang, Zhipeng and Mohajer Hamidi, Shayan and Yu, Han and Wang, Jingjing and Xu, Yuanda and Dong, Xuanzhao and Zhou, Zhengze and He, Ran and Markovic-Voronov, Jelena and Behdin, Kayhan and Ghosh, Sayan and Geramifard, Alborz},
journal = {Findings of the Association for Computational Linguistics: EMNLP 2026},
year = {2026},
month = {Jan},
doi = {10.18653/2026.findings-emnlp.843},
url = {https://doi.org/10.18653/2026.findings-emnlp.843},
}
Zhu, Wenhui et al. (2026). CE-GAD: Curriculum-Efficient On-Policy Adversarial Distillation of Large Language Models. Findings of the Association for Computational Linguistics: EMNLP 2026. https://doi.org/10.18653/2026.findings-emnlp.843
Zhu, Wenhui, et al.. "CE-GAD: Curriculum-Efficient On-Policy Adversarial Distillation of Large Language Models." Findings of the Association for Computational Linguistics: EMNLP 2026, 2026, https://doi.org/10.18653/2026.findings-emnlp.843.
Zhu, Wenhui, et al.. "CE-GAD: Curriculum-Efficient On-Policy Adversarial Distillation of Large Language Models." Findings of the Association for Computational Linguistics: EMNLP 2026 (2026). https://doi.org/10.18653/2026.findings-emnlp.843
Zhu, Wenhui et al., 2026. CE-GAD: Curriculum-Efficient On-Policy Adversarial Distillation of Large Language Models. Findings of the Association for Computational Linguistics: EMNLP 2026. Available at: <https://doi.org/10.18653/2026.findings-emnlp.843>.
TY - JOUR
TI - CE-GAD: Curriculum-Efficient On-Policy Adversarial Distillation of Large Language Models
AU - Zhu, Wenhui
AU - Sang, Hejian
AU - Chen, Xiwen
AU - Wang, Zhipeng
AU - Mohajer Hamidi, Shayan
AU - Yu, Han
AU - Wang, Jingjing
AU - Xu, Yuanda
AU - Dong, Xuanzhao
AU - Zhou, Zhengze
AU - He, Ran
AU - Markovic-Voronov, Jelena
AU - Behdin, Kayhan
AU - Ghosh, Sayan
AU - Geramifard, Alborz
PY - 2026
JO - Findings of the Association for Computational Linguistics: EMNLP 2026
DO - 10.18653/2026.findings-emnlp.843
UR - https://doi.org/10.18653/2026.findings-emnlp.843
ER -