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Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective.

, , , , , , , , and . EMNLP, page 7042-7055. Association for Computational Linguistics, (2022)

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Enhancing Student Competency Models for Game-Based Learning with a Hybrid Stealth Assessment Framework., , , , , , , , , and 1 other author(s). EDM, International Educational Data Mining Society, (2020)Parallel multiple instance learning for extremely large histopathology image analysis., , , , , , , and . BMC Bioinform., 18 (1): 360 (2017)Fairness-aware Model-agnostic Positive and Unlabeled Learning., and . FAccT, page 1698-1708. ACM, (2022)Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System., , , , , and . KDD, page 1791-1800. ACM, (2021)Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective., , , , , , , , and . EMNLP, page 7042-7055. Association for Computational Linguistics, (2022)Deep Active Learning by Leveraging Training Dynamics., , , , , and . NeurIPS, (2022)Semi-Blind Super-Resolution with Kernel-Guided Feature Modification., , , , , and . ICME Workshops, page 1-6. IEEE, (2020)Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence., , , , , , , , , and 15 other author(s). CoRR, (2022)Predicting Challenge Outcomes for Students in a Digital Game for Learning Genetics., , , , , , , , , and . EDM (Workshops), volume 2592 of CEUR Workshop Proceedings, page 51-59. CEUR-WS.org, (2019)FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes., , and . WSDM, page 721-730. ACM, (2024)