Qiao, Yifan, Carlson, Parker, He, Shanxiu, Yang, Yingrui, and Yang, Tao. Threshold-driven Pruning with Segmented Maximum Term Weights for Approximate Cluster-based Sparse Retrieval. Retrieved from https://par.nsf.gov/biblio/10626825. Web. doi:10.18653/v1/2024.emnlp-main.1101.

Qiao, Yifan, Carlson, Parker, He, Shanxiu, Yang, Yingrui, & Yang, Tao. Threshold-driven Pruning with Segmented Maximum Term Weights for Approximate Cluster-based Sparse Retrieval. Retrieved from https://par.nsf.gov/biblio/10626825. https://doi.org/10.18653/v1/2024.emnlp-main.1101

Qiao, Yifan, Carlson, Parker, He, Shanxiu, Yang, Yingrui, and Yang, Tao. "Threshold-driven Pruning with Segmented Maximum Term Weights for Approximate Cluster-based Sparse Retrieval". Country unknown/Code not available: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.. https://doi.org/10.18653/v1/2024.emnlp-main.1101. https://par.nsf.gov/biblio/10626825.

@article{osti_10626825,
place = {Country unknown/Code not available}, title = {Threshold-driven Pruning with Segmented Maximum Term Weights for Approximate Cluster-based Sparse Retrieval}, url = {https://par.nsf.gov/biblio/10626825}, DOI = {10.18653/v1/2024.emnlp-main.1101}, abstractNote = {}, journal = {}, publisher = {Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.}, author = {Qiao, Yifan and Carlson, Parker and He, Shanxiu and Yang, Yingrui and Yang, Tao}, }