Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Mu, Zhancun"'
Vision-language models (VLMs) have excelled in multimodal tasks, but adapting them to embodied decision-making in open-world environments presents challenges. One critical issue is bridging the gap between discrete entities in low-level observations
Externí odkaz:
http://arxiv.org/abs/2410.17856
Learning effective negotiation strategies poses two key challenges: the exploration-exploitation dilemma and dealing with large action spaces. However, there is an absence of learning-based approaches that effectively address these challenges in nego
Externí odkaz:
http://arxiv.org/abs/2407.00567
Autor:
Wang, Zihao, Cai, Shaofei, Mu, Zhancun, Lin, Haowei, Zhang, Ceyao, Liu, Xuejie, Li, Qing, Liu, Anji, Ma, Xiaojian, Liang, Yitao
This paper presents OmniJARVIS, a novel Vision-Language-Action (VLA) model for open-world instruction-following agents in Minecraft. Compared to prior works that either emit textual goals to separate controllers or produce the control command directl
Externí odkaz:
http://arxiv.org/abs/2407.00114
Autor:
Li, Shiqian, Li, Zhi, Mu, Zhancun, Xin, Shiji, Dai, Zhixiang, Leng, Kuangdai, Zhang, Ruihua, Song, Xiaodong, Zhu, Yixin
Global seismic tomography, taking advantage of seismic waves from natural earthquakes, provides essential insights into the earth's internal dynamics. Advanced Full-waveform Inversion (FWI) techniques, whose aim is to meticulously interpret every det
Externí odkaz:
http://arxiv.org/abs/2406.18202