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ECNU at SemEval-2017 Task 8: Rumour Evaluation Using Effective Features and Supervised Ensemble Models.

, , and . SemEval@ACL, page 491-496. Association for Computational Linguistics, (2017)

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Building mutually beneficial relationships between question retrieval and answer ranking to improve performance of community question answering., , , , and . IJCNN, page 832-839. IEEE, (2016)A survey of multi-source domain adaptation., , and . Inf. Fusion, (2015)Unlearning with Fisher Masking., , , and . CoRR, (2023)ECNU at SemEval-2017 Task 5: An Ensemble of Regression Algorithms with Effective Features for Fine-Grained Sentiment Analysis in Financial Domain., , and . SemEval@ACL, page 888-893. Association for Computational Linguistics, (2017)ECNU at SemEval-2017 Task 1: Leverage Kernel-based Traditional NLP features and Neural Networks to Build a Universal Model for Multilingual and Cross-lingual Semantic Textual Similarity., , , and . SemEval@ACL, page 191-197. Association for Computational Linguistics, (2017)Effective Semantic Relationship Classification of Context-Free Chinese Words with Simple Surface and Embedding Features., , and . NLPCC, volume 10619 of Lecture Notes in Computer Science, page 456-464. Springer, (2017)Comparative Investigation of Deep Learning Components for End-to-end Implicit Discourse Relationship Parser., , and . CCL, volume 11856 of Lecture Notes in Computer Science, page 143-155. Springer, (2019)Graph-based Dependency Parsing with Graph Neural Networks., , and . ACL (1), page 2475-2485. Association for Computational Linguistics, (2019)Large-scale Opinion Relation Extraction with Distantly Supervised Neural Network., , , , and . EACL (1), page 1033-1043. Association for Computational Linguistics, (2017)Prompt-based Connective Prediction Method for Fine-grained Implicit Discourse Relation Recognition., , , , and . EMNLP (Findings), page 3848-3858. Association for Computational Linguistics, (2022)