Kamalloo, E., Jafari, A., Zhang, X., Thakur, N., & Lin, J. (2023). HAGRID: A Human-LLM Collaborative Dataset for Generative Information-Seeking With Attribution ArXiv, abs/2307.16883. https://doi.org/10.48550/arXiv.2307.16883
References
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2023
Hebert, L., Golab, L., & Cohen, R. (2023). Predicting Hateful Discussions on Reddit Using Graph Transformer Networks And Communal Context ArXiv, abs/2301.04248. https://doi.org/10.48550/arXiv.2301.04248
Ozsu, T., & Xue, X. (2023). Preface SDA Presented at the Conference Paper Preface SDA conference. Retrieved from https://ceur-ws.org/Vol-3462/SDA0.pdf
Ozsu, T. (2023). Data Science: A Systematic Treatment ArXiv, abs/2301.13761. https://doi.org/10.48550/arXiv.2301.13761
Ren, H., Mousavi, A., Pacaci, A., Chowdhury, S. R., Mohoney, J., Ilyas, I., … Rekatsinas, T. (2023). Fact Ranking Over Large-Scale Knowledge Graphs With Reasoning Embedding Models IEEE Data Engineering Bulletin, 46, 126-139. Retrieved from http://sites.computer.org/debull/A23june/p126.pdf
Tamber, M. S., Pradeep, R., & Lin, J. (2023). Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering Presented at the Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering conference. https://doi.org/10.1007/978-3-031-28241-6_11
Dadvar, V., Golab, L., & Srivastava, D. (2023). POEM: Pattern-Oriented Explanations of Convolutional Neural Networks Proceedings of the VLDB Endowment (PVLDB), 16, 3192-3200. https://doi.org/10.14778/3611479.3611518
Zou, L., Pang, Y., Ozsu, T., & Chen, J. (2023). Efficient Execution of SPARQL Queries With OPTIONAL and UNION Expressions ArXiv, abs/2303.13844. https://doi.org/10.48550/arXiv.2303.13844
Lin, S.-C., Ahmad, A., & Lin, J. (2023). mAggretriever: A Simple Yet Effective Approach to Zero-Shot Multilingual Dense Retrieval Presented at the MAggretriever: A Simple Yet Effective Approach to Zero-Shot Multilingual Dense Retrieval conference. Retrieved from https://aclanthology.org/2023.emnlp-main.715
Hebert, L., Golab, L., Poupart, P., & Cohen, R. (2023). FedFormer: Contextual Federation With Attention in Reinforcement Learning Presented at the FedFormer: Contextual Federation With Attention in Reinforcement Learning conference. https://doi.org/10.5555/3545946.3598716