Yang, M. Y. R., Yang, S., & Lin, J. (2022). Integration of Text and Geospatial Search for Hydrographic Datasets Using the Lucene Search Library Presented at the Integration of Text and Geospatial Search for Hydrographic Datasets Using the Lucene Search Library conference. https://doi.org/10.1145/3529372.3533280
Reference author: Jimmy Lin
First name
Jimmy
Last name
Lin
Tang, R., Kumar, K., Xin, J., Vyas, P., Li, W., Yang, G., … Lin, J. (2022). Temporal Early Exiting for Streaming Speech Commands Recognition Presented at the Temporal Early Exiting for Streaming Speech Commands Recognition conference. https://doi.org/10.1109/ICASSP43922.2022.9746863
Lin, J. (2021). A Proposed Conceptual Framework for a Representational Approach To Information Retrieval SIGIR Forum, 55, 1-4. https://doi.org/10.1145/3527546.3527552
Zhang, X., Ogueji, K., Ma, X., & Lin, J. (2022). Towards Best Practices for Training Multilingual Dense Retrieval Models ArXiv, abs/2204.02363. https://doi.org/10.48550/arXiv.2204.02363
Zhong, W., Yang, J.-H., & Lin, J. (2022). Evaluating Token-Level and Passage-Level Dense Retrieval Models For Math Information Retrieval ArXiv, abs/2203.11163. https://doi.org/10.48550/arXiv.2203.11163
Gao, L., Ma, X., Lin, J., & Callan, J. (2022). Tevatron: An Efficient and Flexible Toolkit for Dense Retrieval ArXiv, abs/2203.05765. https://doi.org/10.48550/arXiv.2203.05765
Li, M., Zhang, X., Xin, J., Zhang, H., & Lin, J. (2022). Certified Error Control of Candidate Set Pruning for Two-Stage Relevance Ranking ArXiv, abs/2205.09638. https://doi.org/10.48550/arXiv.2205.09638
Thakur, N., Reimers, N., & Lin, J. (2022). Domain Adaptation for Memory-Efficient Dense Retrieval ArXiv, abs/2205.11498. https://doi.org/10.48550/arXiv.2205.11498
Thakur, N., Reimers, N., & Lin, J. (2022). Domain Adaptation for Memory-Efficient Dense Retrieval ArXiv, abs/2205.11498. https://doi.org/10.48550/arXiv.2205.11498
Jiang, Z., Dai, Y., Xin, J., Li, M., & Lin, J. (2022). Few-Shot Non-Parametric Learning With Deep Latent Variable Model ArXiv, abs/2206.11573. https://doi.org/10.48550/arXiv.2206.11573