@article{sining2026,
title = {Deeper is Not Always Better: Mitigating the Alignment Tax via Confident Layer Decoding},
author = {Zhoubian, Sining and Zhang, Xuanming and Chen, Yuxuan and Tang, Tianyi and Yang, An and Du, Sean and Zheng, Chujie and Huang, Fei and Liu, Dayiheng and Huang, Gao and Zhou, Jingren},
journal = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing},
year = {2026},
month = {Jan},
}
Zhoubian, Sining et al. (2026). Deeper is Not Always Better: Mitigating the Alignment Tax via Confident Layer Decoding. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing.
Zhoubian, Sining, et al.. "Deeper is Not Always Better: Mitigating the Alignment Tax via Confident Layer Decoding." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing, 2026.
Zhoubian, Sining, et al.. "Deeper is Not Always Better: Mitigating the Alignment Tax via Confident Layer Decoding." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (2026).
Zhoubian, Sining et al., 2026. Deeper is Not Always Better: Mitigating the Alignment Tax via Confident Layer Decoding. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing.
TY - JOUR
TI - Deeper is Not Always Better: Mitigating the Alignment Tax via Confident Layer Decoding
AU - Zhoubian, Sining
AU - Zhang, Xuanming
AU - Chen, Yuxuan
AU - Tang, Tianyi
AU - Yang, An
AU - Du, Sean
AU - Zheng, Chujie
AU - Huang, Fei
AU - Liu, Dayiheng
AU - Huang, Gao
AU - Zhou, Jingren
PY - 2026
JO - Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
ER -