Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study.

Shuo Yu|Mingyue Cheng|Qi Liu|Daoyu Wang|Jiqian Yang|Jie Ouyang|Yucong Luo|Chenyi Lei|Enhong Chen


Anthology ID:DBLP:conf/cikm/0007C0WYOLLC25
Volume:Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025
Year:2025
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:3931-3941
URL:https://doi.org/10.1145/3746252.3761340
DOI:https://doi.org/10.1145/3746252.3761340
DBLP:conf/cikm/0007C0WYOLLC25
BibTeX:
@inproceedings{yu-2025-multisource, author = {Shuo Yu and Mingyue Cheng and Qi Liu and Daoyu Wang and Jiqian Yang and Jie Ouyang and Yucong Luo and Chenyi Lei and Enhong Chen}, editor = {Meeyoung Cha and Carl Yang and Senjuti Basu Roy and Chanyoung Park and Zhenhui Jessie Li and Noseong Park and Carl Yang and Senjuti Basu Roy and Zhenhui Jessie Li and Jaap Kamps and Kijung Shin and Bryan Hooi and Lifang He}, title = {{Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study}}, booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}}, pages = {3931--3941}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3746252.3761340}, doi = {https://doi.org/10.1145/3746252.3761340} }