Pradeep, R., Sharifymoghaddam, S., & Lin, J. (2023). RankVicuna: Zero-Shot Listwise Document Reranking With Open-Source Large Language Models ArXiv, abs/2309.15088. https://doi.org/10.48550/ARXIV.2309.15088
Reference author: Jimmy Lin
First name
Jimmy
Last name
Lin
Ma, X., Teofili, T., & Lin, J. (2023). Anserini Gets Dense Retrieval: Integration of Lucene\textquoterights HNSW Indexes Presented at the Anserini Gets Dense Retrieval: Integration of Lucene\textquoterights HNSW Indexes conference. https://doi.org/10.1145/3583780.3615112
Lin, S.-C., & Lin, J. (2023). A Dense Representation Framework for Lexical and Semantic Matching ACM Transactions on Information Systems (TOIS), 41, 1-110. https://doi.org/10.1145/3582426
Mackenzie, J., Trotman, A., & Lin, J. (2023). Efficient Document-at-a-Time and Score-at-a-Time Query Evaluation For Learned Sparse Representations ACM Transactions on Information Systems (TOIS), 41, 1-96. https://doi.org/10.1145/3576922
Kamphuis, C., Hasibi, F., Lin, J., & de Vries, A. P. (2022). REBL: Entity Linking at Scale (Prototype) Presented at the REBL: Entity Linking at Scale (Prototype) conference. Retrieved from https://ceur-ws.org/Vol-3480/paper-08.pdf
Kamphuis, C., Lin, A., Yang, S., Lin, J., de Vries, A. P., & Hasibi, F. (2023). MMEAD: MS MARCO Entity Annotations and Disambiguations ArXiv, abs/2309.07574. https://doi.org/10.48550/arXiv.2309.07574
Wu, Z., Deshmukh, A. A., Wu, Y., Lin, J., & Mou, L. (2023). Unsupervised Chunking With Hierarchical RNN ArXiv, abs/2309.04919. https://doi.org/10.48550/arXiv.2309.04919
Zhong, W., Xie, Y., & Lin, J. (2023). Answer Retrieval for Math Questions Using Structural and Dense Retrieval Presented at the Retrieval for Math Questions Using Structural and Dense Retrieval conference. https://doi.org/10.1007/978-3-031-42448-9_18
Lin, J., & Teofili, T. (2023). Searching Dense Representations With Inverted Indexes ArXiv, abs/2312.01556. https://doi.org/10.48550/ARXIV.2312.01556
Zhong, W., Xie, Y., & Lin, J. (2023). Answer Retrieval for Math Questions Using Structural and Dense Retrieval Presented at the Retrieval for Math Questions Using Structural and Dense Retrieval conference. https://doi.org/10.1007/978-3-031-42448-9_18