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pro vyhledávání: '"Yan, Chao"'
This short note introduces a novel diagnostic tool for evaluating the convection boundedness properties of numerical schemes across discontinuities. The proposed method is based on the convection boundedness criterion and the normalised variable diag
Externí odkaz:
http://arxiv.org/abs/2411.06152
Autor:
Li, Zhuohang, Zhang, Jiaxin, Yan, Chao, Das, Kamalika, Kumar, Sricharan, Kantarcioglu, Murat, Malin, Bradley A.
Language models (LMs) are known to suffer from hallucinations and misinformation. Retrieval augmented generation (RAG) that retrieves verifiable information from an external knowledge corpus to complement the parametric knowledge in LMs provides a ta
Externí odkaz:
http://arxiv.org/abs/2410.08320
Model quantization has become a crucial technique to address the issues of large memory consumption and long inference times associated with LLMs. Mixed-precision quantization, which distinguishes between important and unimportant parameters, stands
Externí odkaz:
http://arxiv.org/abs/2409.16546
Autor:
Lou, Yan-Chao, Ren, Zhi-Cheng, Chen, Chao, Wan, Pei, Zhu, Wen-Zheng, Wang, Jing, Xue, Shu-Tian, Dong, Bo-Wen, Ding, Jianping, Wang, Xi-Lin, Wang, Hui-Tian
Publikováno v:
Phys. Rev. Applied 22, 014052 (2024)
Recently, great progress has been made in the entanglement of multiple photons at various wavelengths and in different degrees of freedom for optical quantum information applied in diverse scenarios. However, multi-photon entanglement in the transmis
Externí odkaz:
http://arxiv.org/abs/2407.16983
The stock market's ascent typically mirrors the flourishing state of the economy, whereas its decline is often an indicator of an economic downturn. Therefore, for a long time, significant correlation elements for predicting trends in financial stock
Externí odkaz:
http://arxiv.org/abs/2407.16150
Advanced cognition can be extracted from the human brain using brain-computer interfaces. Integrating these interfaces with computer vision techniques, which possess efficient feature extraction capabilities, can achieve more robust and accurate dete
Externí odkaz:
http://arxiv.org/abs/2407.01894
By leveraging the power of Large Language Models(LLMs) and speech foundation models, state of the art speech-text bimodal works can achieve challenging tasks like spoken translation(ST) and question answering(SQA) altogether with much simpler archite
Externí odkaz:
http://arxiv.org/abs/2406.13357
For $S\subseteq \mathbb{F}^n$, consider the linear space of restrictions of degree-$d$ polynomials to $S$. The Hilbert function of $S$, denoted $\mathrm{h}_S(d,\mathbb{F})$, is the dimension of this space. We obtain a tight lower bound on the smalles
Externí odkaz:
http://arxiv.org/abs/2405.10277
Domain adaptation is pivotal for enabling deep learning models to generalize across diverse domains, a task complicated by variations in presentation and cognitive nuances. In this paper, we introduce AD-Aligning, a novel approach that combines adver
Externí odkaz:
http://arxiv.org/abs/2405.09582
Forecasting stock prices remains a considerable challenge in financial markets, bearing significant implications for investors, traders, and financial institutions. Amid the ongoing AI revolution, NVIDIA has emerged as a key player driving innovation
Externí odkaz:
http://arxiv.org/abs/2405.08284