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FedPC: Federated Learning for Language Generation with Personal and Context Preference Embeddings., , и . CoRR, (2022)Using Cross-Loss Influence Functions to Explain Deep Network Representations., , и . CoRR, (2020)Interpretable Reinforcement Learning for Robotics and Continuous Control., , , , , , , , , и 3 other автор(ы). CoRR, (2023)Learning Interpretable, High-Performing Policies for Autonomous Driving., , , , , и . Robotics: Science and Systems, (2022)Towards Balancing Preference and Performance through Adaptive Personalized Explainability., , , и . HRI, стр. 658-668. ACM, (2024)FedPerC: Federated Learning for Language Generation with Personal and Context Preference Embeddings., , и . EACL (Findings), стр. 839-852. Association for Computational Linguistics, (2023)Encoding Human Domain Knowledge to Warm Start Reinforcement Learning., и . AAAI, стр. 5042-5050. AAAI Press, (2021)Towards a Comprehensive Understanding and Accurate Evaluation of Societal Biases in Pre-Trained Transformers., , и . NAACL-HLT, стр. 2383-2389. Association for Computational Linguistics, (2021)Cross-Loss Influence Functions to Explain Deep Network Representations., , и . AISTATS, том 151 из Proceedings of Machine Learning Research, стр. 1-17. PMLR, (2022)Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning., , , , и . AISTATS, том 108 из Proceedings of Machine Learning Research, стр. 1855-1865. PMLR, (2020)