[14] J. Chan, J. C. Chang, T. Hope, D. Shahaf, and A. Kittur. Solvent: A mixed initiative system for finding analogies between research papers. Proc. ACM Hum.-Comput. Interact., 2(CSCW), nov 2018. doi: 10.1145/3274300. URL https://doi.org/10.1145/3274300.
[15] D. Chen and W.-t. Yih. Open-domain question answering. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, pages 34-37, Online, July 2020. Association for Computational Linguistics. doi: 10.18653/v1/2020.acl-tutorials.8. URL https://aclanthology.org/2020.acl-tutorials.8.
[16] A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann, et al. Palm: Scaling language modeling with pathways. arXiv preprint arXiv:2204.02311, 2022.
[17] P. Clark, I. Cowhey, O. Etzioni, T. Khot, A. Sabharwal, C. Schoenick, and O. Tafjord. Think you have solved question answering? try arc, the ai2 reasoning challenge. arXiv preprint arXiv:1803.05457, 2018.
[18] A. Cohan, S. Feldman, I. Beltagy, D. Downey, and D. S. Weld. Specter: Document-level representation learning using citation-informed transformers. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2270–2282, 2020.
[19] N. Craswell, B. Mitra, E. Yilmaz, and D. Campos. Overview of the trec 2020 deep learning track, 2021.
[20] K. Dimitriadou, O. Papaemmanouil, and Y. Diao. Explore-by-example: An automatic query steering framework for interactive data exploration. In Proceedings of the 2014 ACM SIGMOD international conference on Management of data, pages 517-528, 2014.
[21] B. Ding, C. Qin, L. Liu, L. Bing, S. Joty, and B. Li. Is gpt-3 a good data annotator? arXiv preprint arXiv:2212.10450, 2022.
[22] G. Faggioli, L. Dietz, C. Clarke, G. Demartini, M. Hagen, C. Hauff, N. Kando, E. Kanoulas, M. Potthast, B. Stein, and H. Wachsmuth. Perspectives on large language models for relevance judgment, 2023.
[23] T. Formal, C. Lassance, B. Piwowarski, and S. Clinchant. Splade v2: Sparse lexical and expansion model for information retrieval. arXiv preprint arXiv:2109.10086, 2021.
[24] T. Gao, A. Fisch, and D. Chen. Making pre-trained language models better few-shot learners. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 3816-3830, 2021.
[25] T. Gao, X. Yao, and D. Chen. SimCSE: Simple contrastive learning of sentence embeddings. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 6894–6910, Online and Punta Cana, Dominican Republic, Nov. 2021. Association for Computational Linguistics. doi: 10.18653/v1/2021.emnlp-main.552. URL https://aclanthology.org/2021.emnlp-main.552
[26] T. Gebru, J. Morgenstern, B. Vecchione, J. W. Vaughan, H. Wallach, H. Daumee III, and K. Crawford. Datasheets for Datasets. arXiv:1803.09010 [cs], Jan. 2020.
[27] F. Gilardi, M. Alizadeh, and M. Kubli. Chatgpt outperforms crowd-workers for text-annotation tasks. arXiv preprint arXiv:2303.15056, 2023.
[28] R. Greene, T. Sanders, L. Weng, and A. Neelakantan. New and improved embedding model. https://openai.com/blog/new-and-improved-embedding-model/, 2022. Accessed: 2023-06-03.
[29] R. Guha, R. McCool, and E. Miller. Semantic search. In Proceedings of the 12th International Conference on World Wide Web, WWW '03, page 700-709, New York, NY, USA, 2003. Association for Computing Machinery. ISBN 1581136803. doi: 10.1145/775152.775250. URL https://doi.org/10.1145/775152.775250
[30] J. Hsu. Multiple comparisons: theory and methods. CRC Press, 1996.
[31] Y. Hu, Y. Koren, and C. Volinsky. Collaborative filtering for implicit feedback datasets. In 2008 Eighth IEEE international conference on data mining, pages 263-272. IEEE, 2008.
[32] W. Huang, P. Abbeel, D. Pathak, and I. Mordatch. Language models as zero-shot planners: Extracting actionable knowledge for embodied agents. In International Conference on Machine Learning, pages 9118-9147. PMLR, 2022.