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An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems., , , , , , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 3679-3691. Association for Computational Linguistics, (2020)On Pre-training Language Model for Antibody., , and . ICLR, OpenReview.net, (2023)Extractive Summarization as Text Matching., , , , , and . ACL, page 6197-6208. Association for Computational Linguistics, (2020)Learning from Mistakes via Cooperative Study Assistant for Large Language Models., and . EMNLP, page 10667-10685. Association for Computational Linguistics, (2023)INSTRUCTSCORE: Towards Explainable Text Generation Evaluation with Automatic Feedback., , , , , , and . EMNLP, page 5967-5994. Association for Computational Linguistics, (2023)Searching for Effective Neural Extractive Summarization: What Works and What's Next., , , , and . ACL (1), page 1049-1058. Association for Computational Linguistics, (2019)Heterogeneous Graph Neural Networks for Extractive Document Summarization., , , , and . ACL, page 6209-6219. Association for Computational Linguistics, (2020)Learning Personalized Story Evaluation., , , , , , and . CoRR, (2023)Learn from Mistakes through Cooperative Interaction with Study Assistant., and . CoRR, (2023)Exploring Domain Shift in Extractive Text Summarization., , , , , and . CoRR, (2019)