Ozsu, T. . (2023). Data Science: A Systematic Treatment. ArXiv, abs/2301.13761. https://doi.org/10.48550/arXiv.2301.13761
Publications
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Mohoney, J. ., Pacaci, A. ., Chowdhury, S. R., Mousavi, A. ., Ilyas, I. ., Minhas, U. F., Pound, J. ., & Rekatsinas, T. . (2023). High-Throughput Vector Similarity Search in Knowledge Graphs. ArXiv, abs/2304.01926. https://doi.org/10.48550/arXiv.2304.01926
Buchanan, G. R., McKay, D. ., & Clarke, C. . (2023). Made to Measure: A Workshop on Human-Centred Metrics for Information Seeking. Made to Measure: A Workshop on Human-Centred Metrics for Information Seeking. Presented at the. https://doi.org/10.1145/3576840.3578301
Zhang, C. ., Bonifati, A. ., & Ozsu, T. . (2023). Indexing Techniques for Graph Reachability Queries. ArXiv, abs/2311.03542. https://doi.org/10.48550/ARXIV.2311.03542
Ma, X. ., Teofili, T. ., & Lin, J. . (2023). Anserini Gets Dense Retrieval: Integration of Lucene\textquoterights HNSW Indexes. ArXiv, abs/2304.12139. https://doi.org/10.48550/arXiv.2304.12139
Adeyemi, M. ., Oladipo, A. ., Pradeep, R. ., & Lin, J. . (2023). Zero-Shot Cross-Lingual Reranking With Large Language Models for Low-Resource Languages. ArXiv, abs/2312.16159. https://doi.org/10.48550/ARXIV.2312.16159
Pradeep, R. ., Chen, H. ., Gu, L. ., Tamber, M. S., & Lin, J. . (2023). PyGaggle: A Gaggle of Resources for Open-Domain Question Answering. PyGaggle: A Gaggle of Resources for Open-Domain Question Answering. Presented at the. https://doi.org/10.1007/978-3-031-28241-6_10
Mousavi, A. ., Zhan, X. ., Bai, H. ., Shi, P. ., Rekatsinas, T. ., Han, B. ., Li, Y. ., Pound, J. ., Susskind, J. M., Schluter, N. ., Ilyas, I. ., & Jaitly, N. . (2023). Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation. ArXiv, abs/2309.11669. https://doi.org/10.48550/arXiv.2309.11669
Lin, S.-C. ., Asai, A. ., Li, M. ., Oguz, B. ., Lin, J. ., Mehdad, Y. ., Yih, W.- tau ., & Chen, X. . (2023). How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval. How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval. Presented at the. Retrieved from https://aclanthology.org/2023.findings-emnlp.423
Thakur, N. ., Bonifacio, L. ., Zhang, X. ., Ogundepo, O. ., Kamalloo, E. ., Alfonso-Hermelo, D. ., Li, X. ., Liu, Q. ., Chen, B. ., Rezagholizadeh, M. ., & Lin, J. . (2023). NoMIRACL: Knowing When You Don\textquoterightt Know for Robust Multilingual Retrieval-Augmented Generation. ArXiv, abs/2312.11361. https://doi.org/10.48550/ARXIV.2312.11361