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Realistic Evaluation Principles for Cross-document Coreference Resolution., , , , и . *SEM, стр. 143-151. Association for Computational Linguistics, (2021)SpanBERT: Improving Pre-training by Representing and Predicting Spans, , , , , и . (24.07.2019)How to train your self-supervised NLP model: Investigating pre-training objectives, data, and scale. University of Washington, USA, (2022)pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference., , , , и . NAACL-HLT (1), стр. 3597-3608. Association for Computational Linguistics, (2019)Spanbert: Improving pre-training by representing and predicting spans, , , , , и . Transactions of the Association for Computational Linguistics, (2020)FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary., , и . EACL, стр. 455-465. Association for Computational Linguistics, (2021)MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering., , , , , , , , и . ACL (1), стр. 12756-12770. Association for Computational Linguistics, (2023)pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference., , , , и . CoRR, (2018)DESCGEN: A Distantly Supervised Dataset for Generating Abstractive Entity Descriptions., , и . CoRR, (2021)Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities., , , , , , , и . ICCV, стр. 12031-12041. IEEE, (2023)