Jin, G. ., & Salihoglu, S. . (2022). Making RDBMSs Efficient on Graph Workloads Through Predefined Joins. Proceedings of the VLDB Endowment (PVLDB), 15, 1011-1023. Retrieved from https://www.vldb.org/pvldb/vol15/p1011-jin.pdf
Publications
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Dehghan, M. ., Kumar, D. ., & Golab, L. . (2022). GRS: Combining Generation and Revision in Unsupervised Sentence Simplification. GRS: Combining Generation and Revision in Unsupervised Sentence Simplification. Presented at the. Retrieved from https://aclanthology.org/2022.findings-acl.77
Yan, X. ., Luo, C. ., Clarke, C. ., Craswell, N. ., Voorhees, E. M., & Castells, P. . (2022). Human Preferences as Dueling Bandits. ArXiv, abs/2204.10362. https://doi.org/10.48550/arXiv.2204.10362
Vezvaei, A. ., Golab, L. ., Kargar, M. ., Srivastava, D. ., Szlichta, J. ., & Zihayat, M. . (2022). Fine-Tuning Dependencies With Parameters. Fine-Tuning Dependencies With Parameters. Presented at the. https://doi.org/10.48786/edbt.2022.28
Zhong, Y. ., Xiao, J. ., Vetterli, T. ., Matin, M. ., Loo, E. ., Lin, J. ., Bourgon, R. ., & Shapira, O. . (2022). Improving Precancerous Case Characterization via Transformer-Based Ensemble Learning. Improving Precancerous Case Characterization via Transformer-Based Ensemble Learning. Presented at the. Retrieved from https://aclanthology.org/2022.emnlp-industry.38
Mazmudar, M. ., Humphries, T. ., Liu, J. ., Rafuse, M. ., & He, X. . (2022). Cache Me if You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration. ArXiv, abs/2211.15732. https://doi.org/10.48550/arXiv.2211.15732
Toman, D. ., & Weddell, G. . (2022). First Order Rewritability in Ontology-Mediated Querying in Horn Description Logics. First Order Rewritability in Ontology-Mediated Querying in Horn Description Logics. Presented at the. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/20534
Tang, R. ., Pandey, A. ., Jiang, Z. ., Yang, G. ., Kumar, K. ., Lin, J. ., & Türe, F. . (2022). What the DAAM: Interpreting Stable Diffusion Using Cross Attention. ArXiv, abs/2210.04885. https://doi.org/10.48550/arXiv.2210.04885
Kamphuis, C. ., Hasibi, F. ., Lin, J. ., & de Vries, A. P. (2022). REBL: Entity Linking at Scale (Prototype). REBL: Entity Linking at Scale . Presented at the. Retrieved from https://ceur-ws.org/Vol-3480/paper-08.pdf
Zhong, W. ., Yang, J.-H. ., Xie, Y. ., & Lin, J. . (2022). Evaluating Token-Level and Passage-Level Dense Retrieval Models For Math Information Retrieval. Evaluating Token-Level and Passage-Level Dense Retrieval Models For Math Information Retrieval. Presented at the. Retrieved from https://aclanthology.org/2022.findings-emnlp.78