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Li, M., Lin, S.-C., Ma, X., & Lin, J. (2023). SLIM: Sparsified Late Interaction for Multi-Vector Retrieval With Inverted Indexes ArXiv, abs/2302.06587. https://doi.org/10.48550/arXiv.2302.06587

Salem, K. (2023). TECHNICAL PERSPECTIVE: Ad Hoc Transactions: What They Are And Why We Should Care SIGMOD Record, 52, 6. https://doi.org/10.1145/3604437.3604439

Lin, S.-C., Ahmad, A., & Lin, J. (2023). mAggretriever: A Simple Yet Effective Approach to Zero-Shot Multilingual Dense Retrieval Presented at the MAggretriever: A Simple Yet Effective Approach to Zero-Shot Multilingual Dense Retrieval conference. Retrieved from https://aclanthology.org/2023.emnlp-main.715

Hebert, L., Golab, L., Poupart, P., & Cohen, R. (2023). FedFormer: Contextual Federation With Attention in Reinforcement Learning Presented at the FedFormer: Contextual Federation With Attention in Reinforcement Learning conference. https://doi.org/10.5555/3545946.3598716

Lin, J., Alfonso-Hermelo, D., Jeronymo, V., Kamalloo, E., Lassance, C., Nogueira, R. F., … Zhang, X. (2023). Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval ArXiv, abs/2304.01019. https://doi.org/10.48550/arXiv.2304.01019

Ghasemitaheri, S., Holcomb, A., Golab, L., & Keshav, S. (2023). On the Data Quality of Remotely Sensed Forest Maps Presented at the On the Data Quality of Remotely Sensed Forest Maps conference. Retrieved from https://ceur-ws.org/Vol-3462/QDB3.pdf

Salihoglu, S. (2023). K\ uzu: A Database Management System for "Beyond Relational" Workloads SIGMOD Record, 52, 39-40. https://doi.org/10.1145/3631504.3631514

Li, M., Lin, S.-C., Ma, X., & Lin, J. (2023). SLIM: Sparsified Late Interaction for Multi-Vector Retrieval With Inverted Indexes ArXiv, abs/2302.06587. https://doi.org/10.48550/arXiv.2302.06587

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

Pradeep, R., Hui, K., Gupta, J., Lelkes, A. am D., Zhuang, H., Lin, J., … Tran, V. Q. (2023). How Does Generative Retrieval Scale to Millions of Passages? Presented at the How Does Generative Retrieval Scale to Millions of Passages? conference. Retrieved from https://aclanthology.org/2023.emnlp-main.83