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| 2021 || [https://arxiv.org/abs/1912.06680 Augmenting Reinforcement Learning with Human Videos] || Alex X. Lee et al. || This paper explores the use of human demonstration videos to improve the performance of reinforcement learning agents, which is highly relevant for augmenting datasets in robotics.
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| 2024 || [https://arxiv.org/pdf/Real-world_robot_applications_of_foundation_models.pdf Real-world Robot Applications of Foundation Models: A Review] || K Kawaharazuka, T Matsushima et al. || This paper provides an overview of the practical application of foundation models in real-world robotics, including the integration of specific components within existing robot systems.
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| 2024 || [https://arxiv.org/pdf/Is_sora_a_world_simulator.pdf Is SORA a World Simulator? A Comprehensive Survey on General World Models and Beyond] || Z Zhu, X Wang, W Zhao, C Min, N Deng, M Dou et al. || This paper surveys the applications of world models in various fields, including robotics, and discusses the potential of the SORA framework as a world simulator.
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| 2024 || [https://arxiv.org/abs/2401.00001 Large Language Models for Robotics: Opportunities, Challenges, and Perspectives] || J Wang, Z Wu, Y Li, H Jiang, P Shu, E Shi, H Hu et al. || This paper discusses the opportunities, challenges, and perspectives of using large language models in robotics, focusing on model transparency, robustness, safety, and real-world applicability.
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| 2024 || [https://arxiv.org/abs/2401.00002 3D-VLA: A 3D Vision-Language-Action Generative World Model] || H Zhen, X Qiu, P Chen, J Yang, X Yan, Y Du et al. || This paper presents 3D-VLA, a generative world model that combines vision, language, and action to guide robot control and achieve goal objectives.
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| 2024 || [https://arxiv.org/abs/2401.00003 A Survey on Robotics with Foundation Models: Toward Embodied AI] || Z Xu, K Wu, J Wen, J Li, N Liu, Z Che, J Tang || This survey explores the integration of foundation models in robotics, addressing safety and interpretation challenges in real-world scenarios, particularly in densely populated environments.
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| 2024 || [https://arxiv.org/abs/2401.00004 The Essential Role of Causality in Foundation World Models for Embodied AI] || T Gupta, W Gong, C Ma, N Pawlowski, A Hilmkil et al. || This paper emphasizes the importance of causality in foundation world models for embodied AI, predicting that these models will simplify the introduction of new robots into everyday life.
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