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AckSeer: a repository and search engine for automatically extracted acknowledgments from digital libraries., , и . JCDL, стр. 185-194. ACM, (2012)Learning to identify relevant studies for systematic reviews using random forest and external information., , , , и . Mach. Learn., 102 (3): 465-482 (2016)SeerSuite: developing a scalable and reliable application framework for building digital libraries by crawling the web, , , , , и . Proceedings of the 2010 USENIX conference on Web application development, стр. 14--14. Berkeley, CA, USA, USENIX Association, (2010)Quantifying Adaptability in Pre-trained Language Models with 500 Tasks., , , , , и . NAACL-HLT, стр. 4696-4715. Association for Computational Linguistics, (2022)UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning., , , , , , , и . ACL (1), стр. 6253-6264. Association for Computational Linguistics, (2022)The impact of user corrections on a crawl-based digital library: A CiteSeerX perspective., , , и . CollaborateCom, стр. 171-176. ICST / IEEE, (2014)To Pretrain or Not to Pretrain: Examining the Benefits of Pretrainng on Resource Rich Tasks., , и . ACL, стр. 2209-2213. Association for Computational Linguistics, (2020)The feasibility of investing in manual correction of metadata for a large-scale digital library., , и . JCDL, стр. 225-228. IEEE Computer Society, (2014)XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models., , , , , , , и . EMNLP, стр. 13142-13152. Association for Computational Linguistics, (2023)Identifying Earmarks in Congressional Bills., , , , , , и . KDD, стр. 303-311. ACM, (2016)