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ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific Concepts., , , , , , , , , и . EMNLP (Demos), стр. 200-213. Association for Computational Linguistics, (2022)Multi-LexSum: Real-world Summaries of Civil Rights Lawsuits at Multiple Granularities., , , , , и . NeurIPS, (2022)Ontology alignment in the biomedical domain using entity definitions and context., , , , , и . BioNLP, стр. 47-55. Association for Computational Linguistics, (2018)Explaining Relationships Between Scientific Documents., , , , , и . ACL/IJCNLP (1), стр. 2130-2144. Association for Computational Linguistics, (2021)FABLES: Evaluating faithfulness and content selection in book-length summarization., , , , , , , и . CoRR, (2024)Know Your Audience: The benefits and pitfalls of generating plain language summaries beyond the "general" audience., , , и . CHI, стр. 14:1-14:26. ACM, (2024)Don't Stop Pretraining: Adapt Language Models to Domains and Tasks, , , , , , и . (2020)cite arxiv:2004.10964Comment: ACL 2020.LIMEADE: From AI Explanations to Advice Taking., , , и . ACM Trans. Interact. Intell. Syst., 13 (4): 24:1-24:29 (декабря 2023)TREC-COVID: constructing a pandemic information retrieval test collection., , , , , , , , и . SIGIR Forum, 54 (1): 1:1-1:12 (2020)Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval., , , , , , и . EMNLP (Findings), стр. 8177-8199. Association for Computational Linguistics, (2023)