Zobrazeno 1 - 10
of 39 997
pro vyhledávání: '"Zan, A"'
Cloth-changing person re-identification is a subject closer to the real world, which focuses on solving the problem of person re-identification after pedestrians change clothes. The primary challenge in this field is to overcome the complex interplay
Externí odkaz:
http://arxiv.org/abs/2411.00330
We study quantum field theories which have quantum groups as global internal symmetries. We show that in such theories operators are generically non-local, and should be thought as living at the ends of topological lines. We describe the general cons
Externí odkaz:
http://arxiv.org/abs/2410.24142
We study a conformal field theory that arises in the infinite-volume limit of a spin chain with $U_q(sl_2)$ global symmetry. Most operators in the theory are defect-ending operators which allows $U_q(sl_2)$ symmetry transformations to act on them in
Externí odkaz:
http://arxiv.org/abs/2410.24143
Computational capability often falls short when confronted with massive data, posing a common challenge in establishing a statistical model or statistical inference method dealing with big data. While subsampling techniques have been extensively deve
Externí odkaz:
http://arxiv.org/abs/2410.22751
Autor:
Miao, Yibo, Gao, Bofei, Quan, Shanghaoran, Lin, Junyang, Zan, Daoguang, Liu, Jiaheng, Yang, Jian, Liu, Tianyu, Deng, Zhijie
The last year has witnessed the rapid progress of large language models (LLMs) across diverse domains. Among them, CodeLLMs have garnered particular attention because they can not only assist in completing various programming tasks but also represent
Externí odkaz:
http://arxiv.org/abs/2410.18585
Autor:
Gao, Bofei, Song, Feifan, Yang, Zhe, Cai, Zefan, Miao, Yibo, Dong, Qingxiu, Li, Lei, Ma, Chenghao, Chen, Liang, Xu, Runxin, Tang, Zhengyang, Wang, Benyou, Zan, Daoguang, Quan, Shanghaoran, Zhang, Ge, Sha, Lei, Zhang, Yichang, Ren, Xuancheng, Liu, Tianyu, Chang, Baobao
Recent advancements in large language models (LLMs) have led to significant breakthroughs in mathematical reasoning capabilities. However, existing benchmarks like GSM8K or MATH are now being solved with high accuracy (e.g., OpenAI o1 achieves 94.8%
Externí odkaz:
http://arxiv.org/abs/2410.07985
Automated Machine Learning (AutoML) has simplified complex ML processes such as data pre-processing, model selection, and hyper-parameter searching. However, traditional AutoML frameworks focus solely on discriminative tasks, often falling short in t
Externí odkaz:
http://arxiv.org/abs/2410.12841
Autor:
Loeffler, Shane E., Ahmad, Zan, Ali, Syed Yusuf, Yamamoto, Carolyna, Popescu, Dan M., Yee, Alana, Lal, Yash, Trayanova, Natalia, Maggioni, Mauro
Predicting time-dependent dynamics of complex systems governed by non-linear partial differential equations (PDEs) with varying parameters and domains is a challenging task motivated by applications across various fields. We introduce a novel family
Externí odkaz:
http://arxiv.org/abs/2410.04655
Autor:
Liu, Yan, Yi, Xiaoyuan, Chen, Xiaokang, Yao, Jing, Yi, Jingwei, Zan, Daoguang, Liu, Zheng, Xie, Xing, Ho, Tsung-Yi
The demand for regulating potentially risky behaviors of large language models (LLMs) has ignited research on alignment methods. Since LLM alignment heavily relies on reward models for optimization or evaluation, neglecting the quality of reward mode
Externí odkaz:
http://arxiv.org/abs/2409.19024
The rapid development of photo-realistic face generation methods has raised significant concerns in society and academia, highlighting the urgent need for robust and generalizable face forgery detection (FFD) techniques. Although existing approaches
Externí odkaz:
http://arxiv.org/abs/2409.09724