Zhong, Y., Xiao, J., Vetterli, T., Matin, M., Loo, E., Lin, J., … Shapira, O. (2022). Improving Precancerous Case Characterization via Transformer-Based Ensemble Learning Presented at the Mproving Precancerous Case Characterization via Transformer-Based Ensemble Learning conference. Retrieved from https://aclanthology.org/2022.emnlp-industry.38
References
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2022
Xin, J., Tang, R., Jiang, Z., Yu, Y., & Lin, J. (2022). Building an Efficiency Pipeline: Commutativity and Cumulativeness Of Efficiency Operators for Transformers ArXiv, abs/2208.00483. https://doi.org/10.48550/arXiv.2208.00483
Abualsaud, M., & Smucker, M. (2022). The Dark Side of Relevance: The Effect of Non-Relevant Results On Search Behavior Presented at the The Dark Side of Relevance: The Effect of Non-Relevant Results On Search Behavior conference. https://doi.org/10.1145/3498366.3505770
Borgida, A., Franconi, E., Toman, D., & Weddell, G. (2022). Accessing Document Data Sources Using Referring Expression Types Presented at the Accessing Document Data Sources Using Referring Expression Types conference. Retrieved from http://ceur-ws.org/Vol-3263/paper-6.pdf
Wang, R., Wang, J., Idreos, S., Ozsu, T., & Aref, W. G. (2022). The Case for Distributed Shared-Memory Databases With RDMA-Enabled Memory Disaggregation Proceedings of the VLDB Endowment (PVLDB), 16, 15-22. Retrieved from https://www.vldb.org/pvldb/vol16/p15-wang.pdf
Zhong, W., Yang, J.-H., & Lin, J. (2022). Evaluating Token-Level and Passage-Level Dense Retrieval Models For Math Information Retrieval ArXiv, abs/2203.11163. https://doi.org/10.48550/arXiv.2203.11163
Tang, R., Kumar, K., Yang, G., Pandey, A., Mao, Y., Belyaev, V., … Lin, J. (2022). SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale Presented at the SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale conference. Retrieved from https://aclanthology.org/2022.emnlp-industry.29
Vezvaei, A., Golab, L., Kargar, M., Srivastava, D., Szlichta, J., & Zihayat, M. (2022). Fine-Tuning Dependencies With Parameters Presented at the Fine-Tuning Dependencies With Parameters conference. https://doi.org/10.48786/edbt.2022.28
Li, M., Lin, S.-C., Oguz, B., Ghoshal, A., Lin, J., Mehdad, Y., … Chen, X. (2022). CITADEL: Conditional Token Interaction via Dynamic Lexical Routing For Efficient and Effective Multi-Vector Retrieval ArXiv, abs/2211.10411. https://doi.org/10.48550/arXiv.2211.10411
Li, H., Wang, S., Zhuang, S., Mourad, A., Ma, X., Lin, J., & Zuccon, G. (2022). To Interpolate or Not to Interpolate: PRF, Dense and Sparse Retrievers ArXiv, abs/2205.00235. https://doi.org/10.48550/arXiv.2205.00235