Zobrazeno 1 - 10
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pro vyhledávání: '"Dong, Xiaoyu"'
An oblivious subspace embedding is a random $m\times n$ matrix $\Pi$ such that, for any $d$-dimensional subspace, with high probability $\Pi$ preserves the norms of all vectors in that subspace within a $1\pm\epsilon$ factor. In this work, we give an
Externí odkaz:
http://arxiv.org/abs/2411.08773
Autor:
Shi, Guangyuan, Lu, Zexin, Dong, Xiaoyu, Zhang, Wenlong, Zhang, Xuanyu, Feng, Yujie, Wu, Xiao-Ming
Aligning large language models (LLMs) through fine-tuning is essential for tailoring them to specific applications. Therefore, understanding what LLMs learn during the alignment process is crucial. Recent studies suggest that alignment primarily adju
Externí odkaz:
http://arxiv.org/abs/2410.17875
Cognitive biases are systematic deviations in thinking that lead to irrational judgments and problematic decision-making, extensively studied across various fields. Recently, large language models (LLMs) have shown advanced understanding capabilities
Externí odkaz:
http://arxiv.org/abs/2409.16022
We introduce a numerical solver for the steady-state Boltzmann equation based on the symmetric Gauss-Seidel (SGS) method. To solve the nonlinear system on each grid cell derived from the SGS method, a fixed-point iteration preconditioned with its asy
Externí odkaz:
http://arxiv.org/abs/2409.01910
Autor:
Feng, Yujie, Liu, Bo, Dong, Xiaoyu, Lu, Zexin, Zhan, Li-Ming, Lam, Albert Y. S., Wu, Xiao-Ming
An ideal dialogue system requires continuous skill acquisition and adaptation to new tasks while retaining prior knowledge. Dialogue State Tracking (DST), vital in these systems, often involves learning new services and confronting catastrophic forge
Externí odkaz:
http://arxiv.org/abs/2408.09846
Autor:
Liu, Qijiong, Dong, Xiaoyu, Xiao, Jiaren, Chen, Nuo, Hu, Hengchang, Zhu, Jieming, Zhu, Chenxu, Sakai, Tetsuya, Wu, Xiao-Ming
Vector quantization, renowned for its unparalleled feature compression capabilities, has been a prominent topic in signal processing and machine learning research for several decades and remains widely utilized today. With the emergence of large mode
Externí odkaz:
http://arxiv.org/abs/2405.03110
Autor:
Dong, Xiaoyu, Cai, Zhenning
We study the iterative methods for large moment systems derived from the linearized Boltzmann equation. By Fourier analysis, it is shown that the direct application of the block symmetric Gauss-Seidel (BSGS) method has slower convergence for smaller
Externí odkaz:
http://arxiv.org/abs/2312.06191
A random $m\times n$ matrix $S$ is an oblivious subspace embedding (OSE) with parameters $\epsilon>0$, $\delta\in(0,1/3)$ and $d\leq m\leq n$, if for any $d$-dimensional subspace $W\subseteq R^n$, $P\big(\,\forall_{x\in W}\ (1+\epsilon)^{-1}\|x\|\leq
Externí odkaz:
http://arxiv.org/abs/2311.10680
Autor:
Dong, Xiaoyu, Yokoya, Naoto
Understanding dark scenes based on multi-modal image data is challenging, as both the visible and auxiliary modalities provide limited semantic information for the task. Previous methods focus on fusing the two modalities but neglect the correlations
Externí odkaz:
http://arxiv.org/abs/2308.12320
Autor:
Xu, Runsheng, Xia, Xin, Li, Jinlong, Li, Hanzhao, Zhang, Shuo, Tu, Zhengzhong, Meng, Zonglin, Xiang, Hao, Dong, Xiaoyu, Song, Rui, Yu, Hongkai, Zhou, Bolei, Ma, Jiaqi
Modern perception systems of autonomous vehicles are known to be sensitive to occlusions and lack the capability of long perceiving range. It has been one of the key bottlenecks that prevents Level 5 autonomy. Recent research has demonstrated that th
Externí odkaz:
http://arxiv.org/abs/2303.07601