Lin, S.-C., Yang, J.-H., & Lin, J. (2021). Contextualized Query Embeddings for Conversational Search Presented at the Contextualized Query Embeddings for Conversational Search conference. Retrieved from https://aclanthology.org/2021.emnlp-main.77
References
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2021
Sheshbolouki, A., & Ozsu, T. (2021). Scale-Invariant Strength Assortativity of Streaming Butterflies ArXiv, abs/2111.12217. Retrieved from https://arxiv.org/abs/2111.12217
Toman, D., & Weddell, G. (2021). FO Rewritability for OMQ Using Beth Definability and Interpolation Presented at the FO Rewritability for OMQ Using Beth Definability and Interpolatio conference. Retrieved from http://ceur-ws.org/Vol-2954/paper-29.pdf
Mohapatra, S., Sasy, S., He, X., Kamath, G., & Thakkar, O. (2021). The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection ArXiv, abs/2111.04906. Retrieved from https://arxiv.org/abs/2111.04906
Shi, P., Zhang, R., Bai, H., & Lin, J. (2021). Cross-Lingual Training With Dense Retrieval for Document Retrieval ArXiv, abs/2109.01628. Retrieved from https://arxiv.org/abs/2109.01628
Abualsaud, M., Ghajar, K., Minh, L. N. P., Zhang, D., Chen, I. X., Smucker, M., & Tahami, A. V. (2021). UWaterlooMDS at the TREC 2021 Health Misinformation Track Presented at the UWaterlooMDS at the TREC 2021 Health Misinformation Track conference. Retrieved from https://trec.nist.gov/pubs/trec30/papers/UwaterlooMDS-HM.pdf
Lin, J., Nogueira, R., & Yates, A. (2021). Pretrained Transformers for Text Ranking: BERT and Beyond Morgan \& Claypool. https://doi.org/10.2200/S01123ED1V01Y202108HLT053
Parsa, M. S., & Golab, L. (2021). Academic Integrity in Online Education During the COVID-19 Pandemic: A Social Media Mining Study Presented at the Academic Integrity in Online Education During the COVID-19 Pandemic: A Social Media Mining Study conference.
Arabzadeh, N., Yan, X., & Clarke, C. (2021). Predicting Efficiency/Effectiveness Trade-Offs for Dense vs. Sparse Retrieval Strategy Selection Presented at the Predicting Efficiency Effectiveness Trade-Offs for Dense Vs. Sparse Retrieval Strategy Selection conference. https://doi.org/10.1145/3459637.3482159
Suri, S., Ilyas, I., e, C. R., & Rekatsinas, T. (2021). Ember: No-Code Context Enrichment via Similarity-Based Keyless Joins Proceedings of the VLDB Endowment (PVLDB), 15, 699-712. Retrieved from http://www.vldb.org/pvldb/vol15/p699-suri.pdf