Fetching the paper…
Reading the bibliography…
Technology-assisted review (TAR) refers to iterative active learning workflows for document review in high recall retrieval (HRR) tasks.
1904
Earlier work this paper cites.
Rocchio, J.J.: Relevance feedback in information retrieval (1971)
1971
Earlier work this paper cites.
Lewis, D.D., Gale, W.A.: A sequential algorithm for training text classifiers. In: SIGIR 1994, pp. 3–12 (1994)
1994
Earlier work this paper cites.
Ruthven, I., Lalmas, M.: A survey on the use of relevance feedback for information access systems. Knowledge engineering review 18
2003
Earlier work this paper cites.
Lewis, D.D., Yang, Y., Rose, T.G., Li, F.: RCV1: A New Benchmark Collection for Text Categorization Research. JMLR 5
2004
Earlier work this paper cites.
MacAvaney, S., Cohan, A., Goharian, N.: Sledge: a simple yet effective baseline for covid-19 scientific knowledge search. arXiv e-prints pp. arXiv–2005 (2020a)
2005
Earlier work this paper cites.
Cohen, A.M., Hersh, W.R., Peterson, K., Yen, P.Y.: Reducing workload in systematic review preparation using automated citation classification. Journal of the American Medical Informatics Association 13
2006
Earlier work this paper cites.
Robertson, S., Zaragoza, H., et al.: The probabilistic relevance framework: Bm25 and beyond. Foundations and Trends® in Information Retrieval 3
2009
Earlier work this paper cites.
2010
Earlier work this paper cites.
Wallace, B.C., Trikalinos, T.A., Lau, J., Brodley, C., Schmid, C.H.: Semi-automated screening of biomedical citations for systematic reviews. BMC bioinformatics 11
2010
Earlier work this paper cites.
Zhu, J., Wang, H., Hovy, E., Ma, M.: Confidence-based stopping criteria for active learning for data annotation. ACM Transactions on Speech and Language Processing (TSLP) 6
2010
Earlier work this paper cites.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: Machine learning in Python. Journal of Machine Learning Research 12
2011
Earlier work this paper cites.
Oard, D.W., Webber, W.: Information retrieval for e-discovery. Information Retrieval 7
2013
Earlier work this paper cites.
Cormack, G.F., Grossman, M.F.: Evaluation of machine-learning protocols for technology-assisted review in electronic discovery. SIGIR 2014 pp. 153–162 (2014), doi: 10.1145/2600428.2609601
2014
Earlier work this paper cites.
Brown, S.: Peeking inside the black box: A preliminary survey of technology assisted review (tar) and predictive coding algorithms for ediscovery. Suffolk J. Trial & App. Advoc. 21
2015
Earlier work this paper cites.
Roegiest, A., Cormack, G.V.: Trec 2015 total recall track overview (2015)
2015
Earlier work this paper cites.
Saha, T.K., Hasan, M.A., Burgess, C., Habib, M.A., Johnson, J.: Batch-mode active learning for technology-assisted review. In: 2015 IEEE International Conference on Big Data (Big Data), pp. 1134–1143 (Oct 2015), doi: 10.1109/BigData.2015.7363867
2015
Earlier work this paper cites.
Zhu, Y., Kiros, R., Zemel, R., Salakhutdinov, R., Urtasun, R., Torralba, A., Fidler, S.: Aligning books and movies: Towards story-like visual explanations by watching movies and reading books. In: Proceedings of the IEEE international conference on computer vision, pp. 19–27 (2015)
2015
Earlier work this paper cites.
Baron, J., Losey, R., Berman, M.: Perspectives on Predictive Coding: And Other Advanced Search Methods for the Legal Practitioner. American Bar Association, Section of Litigation (2016), ISBN 9781634256582, URL https://books.google.com/books?id=TdJ2AQAACAAJ
2016
Cited alongside, same era.
Gal, Y., Ghahramani, Z.: Dropout as a bayesian approximation: Representing model uncertainty in deep learning. In: international conference on machine learning, pp. 1050–1059, PMLR (2016)
2016
Cited alongside, same era.
Grossman, M.R., Cormack, G.V., Roegiest, A.: Trec 2016 total recall track overview. (2016)
2016
Cited alongside, same era.
Kanoulas, E., Li, D., Azzopardi, L., Spijker, R.: Clef 2017 technologically assisted reviews in empirical medicine overview. In: CEUR workshop proceedings, vol. 1866, pp. 1–29 (2017)
2017
Cited alongside, same era.
Wang, Y., Che, W., Guo, J., Liu, Y., Liu, T.: Cross-lingual bert transformation for zero-shot dependency parsing. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 5725–5731 (2019)
2019
Later among the works it cites.
Zhang, L., Zhang, L.: An ensemble deep active learning method for intent classification. In: Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence, pp. 107–111 (2019)
2019
Later among the works it cites.
Brown, T.B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D.M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., Amodei, D.: Language models are few-shot learners (2020)
2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2017
Cited alongside, same era.
2018
Cited alongside, same era.
Kanoulas, E., Li, D., Azzopardi, L., Spijker, R.: Clef 2018 technologically assisted reviews in empirical medicine overview. CEUR Workshop Proceedings 2125
2018
Cited alongside, same era.
McDonald, G., Macdonald, C., Ounis, I.: Active learning strategies for technology assisted sensitivity review. In: European Conference on Information Retrieval, pp. 439–453, Springer (2018)
2018
Cited alongside, same era.
Oard, D.W., Sebastiani, F., Vinjumur, J.K.: Jointly Minimizing the Expected Costs of Review for Responsiveness and Privilege in E-Discovery. ACM Transactions on Information Systems 37
2018
Cited alongside, same era.
Yang, E., Lewis, D.D., Frieder, O., Grossman, D., Yurchak, R.: Retrieval and richness when querying by document. In: International Conference on Design of Experimental Search & Information REtrieval Systems (2018)
2018
Cited alongside, same era.
2019
Cited alongside, same era.
Bannach-Brown, A., Przybyła, P., Thomas, J., Rice, A.S., Ananiadou, S., Liao, J., Macleod, M.R.: Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error. Systematic reviews 8
2019
Cited alongside, same era.
Callaghan, M.W., Müller-Hansen, F.: Statistical stopping criteria for automated screening in systematic reviews. Systematic Reviews 9
2020
Later among the works it cites.
Ein-Dor, L., Halfon, A., Gera, A., Shnarch, E., Dankin, L., Choshen, L., Danilevsky, M., Aharonov, R., Katz, Y., Slonim, N.: Active learning for bert: An empirical study. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 7949–7962 (2020)
2020
Later among the works it cites.
2020
Later among the works it cites.
Gururangan, S., Marasović, A., Swayamdipta, S., Lo, K., Beltagy, I., Downey, D., Smith, N.A.: Don’t stop pretraining: Adapt language models to domains and tasks. In: Proceedings of ACL (2020)
2020
Later among the works it cites.
Hou, Y., Che, W., Lai, Y., Zhou, Z., Liu, Y., Liu, H., Liu, T.: Few-shot slot tagging with collapsed dependency transfer and label-enhanced task-adaptive projection network. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 1381–1393 (2020)
2020
Later among the works it cites.
Li, D., Kanoulas, E.: When to stop reviewing in technology-assisted reviews: Sampling from an adaptive distribution to estimate residual relevant documents. ACM Transactions on Information Systems (TOIS) 38
2020
Later among the works it cites.
2020
Later among the works it cites.
2020
Later among the works it cites.
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., Liu, P.J.: Exploring the limits of transfer learning with a unified text-to-text transformer. Journal of Machine Learning Research 21
2020
Later among the works it cites.
Shu, K., Mukherjee, S., Zheng, G., Awadallah, A.H., Shokouhi, M., Dumais, S.: Learning with weak supervision for email intent detection. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1051–1060 (2020)
2020
Later among the works it cites.
2020
Later among the works it cites.
Yang, Z., Wang, Y., Chen, X., Liu, J., Qiao, Y.: Context-transformer: tackling object confusion for few-shot detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 12653–12660 (2020)
2020
Later among the works it cites.
2021
Closest in time.
Lewis, D.D., Yang, E., Frieder, O.: Certifying one-phase technology-assisted reviews. In: Proceedings of 30th ACM International Conference on Information and Knowledge Management (2021)
2021
Closest in time.