Ma, X., Pradeep, R., Nogueira, R., & Lin, J. (2022). Document Expansion Baselines and Learned Sparse Lexical Representations For MS MARCO V1 and V2 Presented at the Expansion Baselines and Learned Sparse Lexical Representations For MS MARCO V1 and V2 conference. https://doi.org/10.1145/3477495.3531749
References
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2022
Arabzadeh, N., Seifikar, M., & Clarke, C. (2022). Unsupervised Question Clarity Prediction Through Retrieved Item Coherency ArXiv, abs/2208.04882. https://doi.org/10.48550/arXiv.2208.04882
Nanayakkara, P., Bater, J., He, X., Hullman, J., & Rogers, J. (2022). Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases ArXiv, abs/2201.05964. Retrieved from https://arxiv.org/abs/2201.05964
Shi, P., Zhang, R., Bai, H., & Lin, J. (2022). XRICL: Cross-Lingual Retrieval-Augmented in-Context Learning For Cross-Lingual Text-to-SQL Semantic Parsing Presented at the XRICL: Cross-Lingual Retrieval-Augmented In-Context Learning For Cross-Lingual Text-to-SQL Semantic Parsing conference. Retrieved from https://aclanthology.org/2022.findings-emnlp.384
Dadvar, V., Golab, L., & Srivastava, D. (2022). Exploring Data Using Patterns: A Survey Information Systems, 108, 101985. https://doi.org/10.1016/j.is.2022.101985
Li, M., Lin, S.-C., Oguz, B., Ghoshal, A., Lin, J., Mehdad, Y., … Chen, X. (2022). CITADEL: Conditional Token Interaction via Dynamic Lexical Routing For Efficient and Effective Multi-Vector Retrieval ArXiv, abs/2211.10411. https://doi.org/10.48550/arXiv.2211.10411
Abualsaud, M., & Smucker, M. (2022). The Dark Side of Relevance: The Effect of Non-Relevant Results On Search Behavior Presented at the The Dark Side of Relevance: The Effect of Non-Relevant Results On Search Behavior conference. https://doi.org/10.1145/3498366.3505770
Li, H., Wang, S., Zhuang, S., Mourad, A., Ma, X., Lin, J., & Zuccon, G. (2022). To Interpolate or Not to Interpolate: PRF, Dense and Sparse Retrievers ArXiv, abs/2205.00235. https://doi.org/10.48550/arXiv.2205.00235
Chen, Y., Xiao, G., Ozsu, T., Tang, Z., Zomaya, A. Y., & Li, K. (2022). Exploiting Hierarchical Parallelism and Reusability in Tensor Kernel Processing on Heterogeneous HPC Systems Presented at the Exploiting Hierarchical Parallelism and Reusability in Tensor Kernel Processing on Heterogeneous HPC Systems conference. https://doi.org/10.1109/ICDE53745.2022.00234
Dadvar, V., Golab, L., & Srivastava, D. (2022). POEM: Pattern-Oriented Explanations of CNN Models Proceedings of the VLDB Endowment (PVLDB), 15, 3618-3621. Retrieved from https://www.vldb.org/pvldb/vol15/p3618-golab.pdf