@article{yin2026,
title = {CONFRAG: Confidence-Guided Retrieval-Augmented Generation},
author = {Huang, Yin and Xu, Yifan Ethan and Sun, Kai and Yan, Vera and Sun, Alicia Yi and Khan, Haidar and Nguyen, Jimmy and Chen, Jingxiang and Kachuee, Mohammad and Lin, Zhaojiang and Liu, Yue and Colak, Aaron and Kumar, Anuj and Yih, Wen-tau and Dong, Xin Luna},
journal = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track},
year = {2026},
month = {Jan},
doi = {10.18653/2026.emnlp-industry.171},
url = {https://doi.org/10.18653/2026.emnlp-industry.171},
}
Huang, Yin et al. (2026). CONFRAG: Confidence-Guided Retrieval-Augmented Generation. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track. https://doi.org/10.18653/2026.emnlp-industry.171
Huang, Yin, et al.. "CONFRAG: Confidence-Guided Retrieval-Augmented Generation." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track, 2026, https://doi.org/10.18653/2026.emnlp-industry.171.
Huang, Yin, et al.. "CONFRAG: Confidence-Guided Retrieval-Augmented Generation." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track (2026). https://doi.org/10.18653/2026.emnlp-industry.171
Huang, Yin et al., 2026. CONFRAG: Confidence-Guided Retrieval-Augmented Generation. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track. Available at: <https://doi.org/10.18653/2026.emnlp-industry.171>.
TY - JOUR
TI - CONFRAG: Confidence-Guided Retrieval-Augmented Generation
AU - Huang, Yin
AU - Xu, Yifan Ethan
AU - Sun, Kai
AU - Yan, Vera
AU - Sun, Alicia Yi
AU - Khan, Haidar
AU - Nguyen, Jimmy
AU - Chen, Jingxiang
AU - Kachuee, Mohammad
AU - Lin, Zhaojiang
AU - Liu, Yue
AU - Colak, Aaron
AU - Kumar, Anuj
AU - Yih, Wen-tau
AU - Dong, Xin Luna
PY - 2026
JO - Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track
DO - 10.18653/2026.emnlp-industry.171
UR - https://doi.org/10.18653/2026.emnlp-industry.171
ER -