Conia, S. ., Li, M. ., Lee, D. ., Minhas, U. F., Ilyas, I. ., & Li, Y. . (2023). Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs. Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs. Presented at the. Retrieved from https://aclanthology.org/2023.emnlp-main.100
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Adeyemi, M. ., Oladipo, A. ., Zhang, X. ., Alfonso-Hermelo, D. ., Rezagholizadeh, M. ., Chen, B. ., & Lin, J. . (2023). CIRAL at FIRE 2023: Cross-Lingual Information Retrieval for African Languages. CIRAL at FIRE 2023: Cross-Lingual Information Retrieval for African Languages Primary Tabs . Presented at the. https://doi.org/10.1145/3632754.3633076
Lin, J. ., & Teofili, T. . (2023). Searching Dense Representations With Inverted Indexes. ArXiv, abs/2312.01556. https://doi.org/10.48550/ARXIV.2312.01556
Sadri, N. ., & Cormack, G. . (2022). Continuous Active Learning Using Pretrained Transformers. ArXiv, abs/2208.06955. https://doi.org/10.48550/arXiv.2208.06955
Guo, R. ., Guo, V. ., Kim, A. ., Hildred, J. ., & Daudjee, K. . (2022). Hydrozoa: Dynamic Hybrid-Parallel DNN Training on Serverless Containers. Hydrozoa: Dynamic Hybrid-Parallel DNN Training on Serverless Containers. Presented at the. Retrieved from https://proceedings.mlsys.org/paper/2022/hash/ea5d2f1c4608232e07d3aa3d998e5135-Abstract.html
Yan, D. ., Guo, G. ., Khalil, J. ., Ozsu, T. ., Ku, W.-S. ., & Lui, J. C. S. (2022). G-Thinker: A General Distributed Framework for Finding Qualified Subgraphs In a Big Graph With Load Balancing. The VLDB Journal, 31, 287-320. https://doi.org/10.1007/s00778-021-00688-z
Karegar, R. ., Mirsafian, M. ., Godfrey, P. ., Golab, L. ., Kargar, M. ., Srivastava, D. ., & Szlichta, J. . (2022). Discovering Domain Orders via Order Dependencies. Discovering Domain Orders via Order Dependencies. Presented at the. https://doi.org/10.1109/ICDE53745.2022.00087
Tang, R. ., Kumar, K. ., Yang, G. ., Pandey, A. ., Mao, Y. ., Belyaev, V. ., Emmadi, M. ., Murray, C. ., Türe, F. ., & Lin, J. . (2022). SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale. SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale. Presented at the. Retrieved from https://aclanthology.org/2022.emnlp-industry.29
Sheshbolouki, A. ., & Ozsu, T. . (2022). sGrapp: Butterfly Approximation in Streaming Graphs. ACM Transactions on Knowledge Discovery from Data, 16, 1-76. https://doi.org/10.1145/3495011
Seltzer, J. ., Cheng, K. ., Zong, S. ., & Lin, J. . (2022). Flipping the Script: Inverse Information Seeking Dialogues for Market Research. Flipping the Script: Inverse Information Seeking Dialogues for Market Research. Presented at the. https://doi.org/10.1145/3477495.3536326