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of 224
pro vyhledávání: '"Chen, Kaiqi"'
Recent advances in diffusion-based robot policies have demonstrated significant potential in imitating multi-modal behaviors. However, these approaches typically require large quantities of demonstration data paired with corresponding robot action la
Externí odkaz:
http://arxiv.org/abs/2410.07584
Large language models (LLMs) are increasingly employed for complex tasks that process multiple generation calls in a tree structure with shared prefixes of tokens, including few-shot prompting, multi-step reasoning, speculative decoding, etc. However
Externí odkaz:
http://arxiv.org/abs/2404.00242
Recent advances in large language models have brought immense value to the world, with their superior capabilities stemming from the massive number of parameters they utilize. However, even the GPUs with the highest memory capacities, currently peaki
Externí odkaz:
http://arxiv.org/abs/2403.06504
Imitation learning empowers artificial agents to mimic behavior by learning from demonstrations. Recently, diffusion models, which have the ability to model high-dimensional and multimodal distributions, have shown impressive performance on imitation
Externí odkaz:
http://arxiv.org/abs/2402.16075
Perspective-taking is the ability to perceive or understand a situation or concept from another individual's point of view, and is crucial in daily human interactions. Enabling robots to perform perspective-taking remains an unsolved problem; existin
Externí odkaz:
http://arxiv.org/abs/2308.06498
Visual Simultaneous Localization and Mapping (vSLAM) has achieved great progress in the computer vision and robotics communities, and has been successfully used in many fields such as autonomous robot navigation and AR/VR. However, vSLAM cannot achie
Externí odkaz:
http://arxiv.org/abs/2209.06428
Communication is a hallmark of intelligence. In this work, we present MIRROR, an approach to (i) quickly learn human models from human demonstrations, and (ii) use the models for subsequent communication planning in assistive shared-control settings.
Externí odkaz:
http://arxiv.org/abs/2203.02877
Autor:
Huang, Wenyan, Hu, Jiahao, Zhu, Yeqi, Zhan, Jiahua, Lei, Rongdan, Sun, Yuchen, Chen, Kaiqi, Lan, Siqi, Yao, Rongqian
Publikováno v:
In Journal of Alloys and Compounds 15 November 2024 1005
Publikováno v:
In Composites Science and Technology 20 October 2024 257
Autor:
Huang, Wenyan, Liang, Jiahao, Chen, Kaiqi, Yu, Ying, Zhu, Yeqi, Li, Junhui, Pan, Cheng, Guo, Yipeng, Lan, Siqi, Yao, Rongqian
Publikováno v:
In Composites Part B December 2024 287