Mohoney, J., Pacaci, A., Chowdhury, S. R., Mousavi, A., Ilyas, I., Minhas, U. F., … Rekatsinas, T. (2023). High-Throughput Vector Similarity Search in Knowledge Graphs ArXiv, abs/2304.01926. https://doi.org/10.48550/arXiv.2304.01926
References
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2023
Buchanan, G. R., McKay, D., & Clarke, C. (2023). Made to Measure: A Workshop on Human-Centred Metrics for Information Seeking Presented at the Made to Measure: A Workshop on Human-Centred Metrics for Information Seeking conference. 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
Pradeep, R., Chen, H., Gu, L., Tamber, M. S., & Lin, J. (2023). PyGaggle: A Gaggle of Resources for Open-Domain Question Answering Presented at the PyGaggle: A Gaggle of Resources for Open-Domain Question Answering conference. https://doi.org/10.1007/978-3-031-28241-6_10
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
Adeyemi, M., Oladipo, A., Zhang, X. C., Alfonso-Hermelo, D., Rezagholizadeh, M., Chen, B., & Lin, J. (2023). Overview of the CIRAL Track at FIRE 2023: Cross-Lingual Information Retrieval for African Languages Presented at the CIRAL Track at FIRE 2023: Cross-Lingual Information Retrieval for African Languages conference. Retrieved from https://ceur-ws.org/Vol-3681/T2-1.pdf
Mousavi, A., Zhan, X., Bai, H., Shi, P., Rekatsinas, T., Han, B., … 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
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
Lin, S.-C., Asai, A., Li, M., Oguz, B., Lin, J., Mehdad, Y., … Chen, X. (2023). How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval Presented at the How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval conference. Retrieved from https://aclanthology.org/2023.findings-emnlp.423
Thakur, N., Bonifacio, L., Zhang, X., Ogundepo, O., Kamalloo, E., Alfonso-Hermelo, D., … 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