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
References
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2022
Trotman, A., Mackenzie, J., Parameswaran, P., & Lin, J. (2022). A Common Framework for Exploring Document-at-a-Time and Score-at-a-Time Retrieval Methods Presented at the A Common Framework for Exploring Document-at-a-Time and Score-at-a-Time Retrieval Methods conference. https://doi.org/10.1145/3477495.3531657
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
Parsa, M. S., Shi, H., Xu, Y., Yim, A., Yin, Y., & Golab, L. (2022). Analyzing Climate Change Discussions on Reddit Presented at the Analyzing Climate Change Discussions on Reddit conference. https://doi.org/10.1109/CSCI58124.2022.00150
Liu, Y., Hu, C., & Lin, J. (2022). Another Look at Information Retrieval as Statistical Translation Presented at the Another Look at Information Retrieval As Statistical Translation conference. 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
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
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
Lin, J. (2022). Building a Culture of Reproducibility in Academic Research ArXiv, abs/2212.13534. https://doi.org/10.48550/arXiv.2212.13534
Gao, L., Ma, X., Lin, J., & Callan, J. (2022). Tevatron: An Efficient and Flexible Toolkit for Dense Retrieval ArXiv, abs/2203.05765. https://doi.org/10.48550/arXiv.2203.05765