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Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases., , , и . ACL (1), стр. 14254-14267. Association for Computational Linguistics, (2023)A Survey on Fairness in Large Language Models., , , , и . CoRR, (2023)Fine Clustering Analysis of Internet Financial Credit Investigation Based on Big Data., , , , , и . Big Data Res., (2022)Measuring and mitigating language model biases in abusive language detection., , , , и . Inf. Process. Manag., 60 (3): 103277 (мая 2023)Mitigating social biases of pre-trained language models via contrastive self-debiasing with double data augmentation., , , , , и . Artif. Intell., (2024)Structural-aware motif-based prompt tuning for graph clustering., , , , , и . Inf. Sci., (ноября 2023)Evaluation of smart city construction and optimization of city brand model under neural networks., , , и . Comput. Sci. Inf. Syst., 20 (2): 573-593 (2023)Bank customer loyalty under the background of internet finance and multimedia technology., и . J. Intell. Fuzzy Syst., 40 (4): 5807-5817 (2021)TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text Classification., , , , и . AAAI, стр. 18999-19007. AAAI Press, (2024)Exploring Multiple Hypergraphs for Heterogeneous Graph Neural Networks., , , и . Expert Syst. Appl., (февраля 2024)