RAD-Bench: Evaluating Large Language Models’ Capabilities in Retrieval Augmented Dialogues

Tzu-Lin Kuo, FengTing Liao, Mu-Wei Hsieh, Fu-Chieh Chang, Po-Chun Hsu, Da-shan Shiu


Anthology ID:
2025.naacl-industry.66
Volume:
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track)
Month:
April
Year:
2025
Address:
Albuquerque, New Mexico
Editors:
Weizhu Chen, Yi Yang, Mohammad Kachuee, Xue-Yong Fu
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
868–902
Language:
URL:
https://preview.aclanthology.org/corrections-2025-06/2025.naacl-industry.66/
DOI:
10.18653/v1/2025.naacl-industry.66
Bibkey:
Cite (ACL):
Tzu-Lin Kuo, FengTing Liao, Mu-Wei Hsieh, Fu-Chieh Chang, Po-Chun Hsu, and Da-shan Shiu. 2025. RAD-Bench: Evaluating Large Language Models’ Capabilities in Retrieval Augmented Dialogues. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track), pages 868–902, Albuquerque, New Mexico. Association for Computational Linguistics.
Cite (Informal):
RAD-Bench: Evaluating Large Language Models’ Capabilities in Retrieval Augmented Dialogues (Kuo et al., NAACL 2025)
Copy Citation:
PDF:
https://preview.aclanthology.org/corrections-2025-06/2025.naacl-industry.66.pdf