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pro vyhledávání: '"MA, Ying"'
This demo presents a novel end-to-end framework that combines on-device large language models (LLMs) with smartphone sensing technologies to achieve context-aware and personalized services. The framework addresses critical limitations of current pers
Externí odkaz:
http://arxiv.org/abs/2407.04418
Autor:
Ma, Ying, Burns, Owen, Wang, Mingqiu, Li, Gang, Du, Nan, Shafey, Laurent El, Wang, Liqiang, Shafran, Izhak, Soltau, Hagen
Reinforcement learning (RL) is an effective method of finding reasoning pathways in incomplete knowledge graphs (KGs). To overcome the challenges of a large action space, a self-supervised pre-training method is proposed to warm up the policy network
Externí odkaz:
http://arxiv.org/abs/2405.13640
We propose and analyze an extended Fourier pseudospectral (eFP) method for the spatial discretization of the Gross-Pitaevskii equation (GPE) with low regularity potential by treating the potential in an extended window for its discrete Fourier transf
Externí odkaz:
http://arxiv.org/abs/2310.20177