Gao, L. ., Ma, X. ., Lin, J. ., & Callan, J. . (2022). Precise Zero-Shot Dense Retrieval Without Relevance Labels. ArXiv, abs/2212.10496. https://doi.org/10.48550/arXiv.2212.10496
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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
Liu, Y. ., Hu, C. ., & Lin, J. . (2022). Another Look at Information Retrieval as Statistical Translation. Another Look at Information Retrieval As Statistical Translation. Presented at the. https://doi.org/10.1145/3477495.3531717
Shehata, D. ., Arabzadeh, N. ., & Clarke, C. . (2022). Early Stage Sparse Retrieval With Entity Linking. ArXiv, abs/2208.04887. https://doi.org/10.48550/arXiv.2208.04887
Li, M. ., Zhang, X. ., Xin, J. ., Zhang, H. ., & Lin, J. . (2022). Certified Error Control of Candidate Set Pruning for Two-Stage Relevance Ranking. Certified Error Control of Candidate Set Pruning for Two-Stage Relevance Ranking. Presented at the. Retrieved from https://aclanthology.org/2022.emnlp-main.23
Lin, J. ., Campos, D. ., Craswell, N. ., Mitra, B. ., & Yilmaz, E. . (2022). Fostering Coopetition While Plugging Leaks: The Design and Implementation Of the MS MARCO Leaderboards. Fostering Coopetition While Plugging Leaks: The Design and Implementation Of the MS MARCO Leaderboards. Presented at the. https://doi.org/10.1145/3477495.3531725
Artikis, A. ., Tatbul, N. ., Golab, L. ., & Sadoghi, M. . (2022). Editorial. Information Systems, 109, 102088. https://doi.org/10.1016/j.is.2022.102088
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
Craswell, N. ., Mitra, B. ., Yilmaz, E. ., Campos, D. ., Lin, J. ., Voorhees, E. M., & Soboroff, I. . (2022). Overview of the TREC 2022 Deep Learning Track. Overview of the TREC 2022 Deep Learning Track. Presented at the. Retrieved from https://trec.nist.gov/pubs/trec31/papers/Overview_deep.pdf
Arabzadeh, N. ., Seifikar, M. ., & Clarke, C. . (2022). Unsupervised Question Clarity Prediction Through Retrieved Item Coherency. Unsupervised Question Clarity Prediction Through Retrieved Item Coherency. Presented at the. https://doi.org/10.1145/3511808.3557719