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pro vyhledávání: '"Sun, Xingpeng"'
Embodied Question Answering (EQA) is an essential yet challenging task for robotic home assistants. Recent studies have shown that large vision-language models (VLMs) can be effectively utilized for EQA, but existing works either focus on video-based
Externí odkaz:
http://arxiv.org/abs/2410.20263
Publikováno v:
IROS 2024
While LLMs are proficient at processing text in human conversations, they often encounter difficulties with the nuances of verbal instructions and, thus, remain prone to hallucinate trust in human command. In this work, we present TrustNavGPT, an LLM
Externí odkaz:
http://arxiv.org/abs/2408.01867
Publikováno v:
Transactions on Machine Learning Research 2024
While LLMs excel in processing text in these human conversations, they struggle with the nuances of verbal instructions in scenarios like social navigation, where ambiguity and uncertainty can erode trust in robotic and other AI systems. We can addre
Externí odkaz:
http://arxiv.org/abs/2402.03494
Autor:
Ling, Lu, Sheng, Yichen, Tu, Zhi, Zhao, Wentian, Xin, Cheng, Wan, Kun, Yu, Lantao, Guo, Qianyu, Yu, Zixun, Lu, Yawen, Li, Xuanmao, Sun, Xingpeng, Ashok, Rohan, Mukherjee, Aniruddha, Kang, Hao, Kong, Xiangrui, Hua, Gang, Zhang, Tianyi, Benes, Bedrich, Bera, Aniket
We have witnessed significant progress in deep learning-based 3D vision, ranging from neural radiance field (NeRF) based 3D representation learning to applications in novel view synthesis (NVS). However, existing scene-level datasets for deep learnin
Externí odkaz:
http://arxiv.org/abs/2312.16256
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