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xSense: Learning Sense-Separated Sparse Representations and Textual Definitions for Explainable Word Sense Networks., , , и . CoRR, (2018)Go Beyond Plain Fine-Tuning: Improving Pretrained Models for Social Commonsense., , , , , и . SLT, стр. 1028-1035. IEEE, (2021)Do Localization Methods Actually Localize Memorized Data in LLMs?, , и . CoRR, (2023)CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks., , , , , и . NeurIPS, (2022)What Does This Word Mean? Explaining Contextualized Embeddings with Natural Language Definition., и . EMNLP/IJCNLP (1), стр. 6063-6069. Association for Computational Linguistics, (2019)Data Curation Alone Can Stabilize In-context Learning., и . ACL (1), стр. 8123-8144. Association for Computational Linguistics, (2023)Median thinking style predicts the individual differences in processing capacity., и . CogSci, cognitivesciencesociety.org, (2014)Incorporating Commonsense Knowledge Graph in Pretrained Models for Social Commonsense Tasks., , , , , и . CoRR, (2021)Rethinking Why Intermediate-Task Fine-Tuning Works., и . EMNLP (Findings), стр. 706-713. Association for Computational Linguistics, (2021)A Meaning-based English Math Word Problem Solver with Understanding, Reasoning and Explanation., , , , и . COLING (Demos), стр. 151-155. ACL, (2016)