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Are Negative Samples Necessary in Entity Alignment?: An Approach with High Performance, Scalability and Robustness., , , and . CIKM, page 1263-1273. ACM, (2021)ECNU at SemEval-2018 Task 12: An End-to-End Attention-based Neural Network for the Argument Reasoning Comprehension Task., , and . SemEval@NAACL-HLT, page 1094-1098. Association for Computational Linguistics, (2018)Memory-Based Model with Multiple Attentions for Multi-turn Response Selection., , and . ICONIP (2), volume 11302 of Lecture Notes in Computer Science, page 296-307. Springer, (2018)MRAEA: An Efficient and Robust Entity Alignment Approach for Cross-lingual Knowledge Graph., , , , and . WSDM, page 420-428. ACM, (2020)Is "hot pizza" Positive or Negative? Mining Target-aware Sentiment Lexicons., , , and . EACL, page 608-618. Association for Computational Linguistics, (2021)Structural Opinion Mining for Graph-based Sentiment Representation., , , and . EMNLP, page 1332-1341. ACL, (2011)LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagation., , , and . EMNLP, page 825-838. Association for Computational Linguistics, (2022)Extracting Entities and Relations with Joint Minimum Risk Training., , , , , , and . EMNLP, page 2256-2265. Association for Computational Linguistics, (2018)The CoNLL-2013 Shared Task on Grammatical Error Correction., , , , and . CoNLL Shared Task, page 1-12. ACL, (2013)A Multi-Task Dataset for Assessing Discourse Coherence in Chinese Essays: Structure, Theme, and Logic Analysis., , , , , and . EMNLP, page 6673-6688. Association for Computational Linguistics, (2023)