Zobrazeno 1 - 10
of 1 278
pro vyhledávání: '"WANG Zhongyuan"'
Publikováno v:
Xibei zhiwu xuebao, Vol 44, Iss 11, Pp 1789-1800 (2024)
[Objective] To reveal the regional variation of adaptation strategies of common species Populus alba, it can provide data support for predicting plant adaptation potential under the background of climate change. [Methods] Nine state-owned forest fa
Externí odkaz:
https://doaj.org/article/3aaa581882b3481b8ef1a4749fdc1d38
This paper presents EasyRAG, a simple, lightweight, and efficient retrieval-augmented generation framework for automated network operations. Our framework has three advantages. The first is accurate question answering. We designed a straightforward R
Externí odkaz:
http://arxiv.org/abs/2410.10315
Autor:
Wang, Xinlong, Zhang, Xiaosong, Luo, Zhengxiong, Sun, Quan, Cui, Yufeng, Wang, Jinsheng, Zhang, Fan, Wang, Yueze, Li, Zhen, Yu, Qiying, Zhao, Yingli, Ao, Yulong, Min, Xuebin, Li, Tao, Wu, Boya, Zhao, Bo, Zhang, Bowen, Wang, Liangdong, Liu, Guang, He, Zheqi, Yang, Xi, Liu, Jingjing, Lin, Yonghua, Huang, Tiejun, Wang, Zhongyuan
While next-token prediction is considered a promising path towards artificial general intelligence, it has struggled to excel in multimodal tasks, which are still dominated by diffusion models (e.g., Stable Diffusion) and compositional approaches (e.
Externí odkaz:
http://arxiv.org/abs/2409.18869
The generalization ability of deepfake detectors is vital for their applications in real-world scenarios. One effective solution to enhance this ability is to train the models with manually-blended data, which we termed "blendfake", encouraging model
Externí odkaz:
http://arxiv.org/abs/2408.17052
Recent Text-to-SQL methods leverage large language models (LLMs) by incorporating feedback from the database management system. While these methods effectively address execution errors in SQL queries, they struggle with database mismatches -- errors
Externí odkaz:
http://arxiv.org/abs/2408.16991
Learning intrinsic bias from limited data has been considered the main reason for the failure of deepfake detection with generalizability. Apart from the discovered content and specific-forgery bias, we reveal a novel spatial bias, where detectors in
Externí odkaz:
http://arxiv.org/abs/2408.06779
The face swapping technique based on deepfake methods poses significant social risks to personal identity security. While numerous deepfake detection methods have been proposed as countermeasures against malicious face swapping, they can only output
Externí odkaz:
http://arxiv.org/abs/2408.06635
Recent years have seen an increasing interest in physical adversarial attacks, which aim to craft deployable patterns for deceiving deep neural networks, especially for person detectors. However, the adversarial patterns of existing patch-based attac
Externí odkaz:
http://arxiv.org/abs/2408.06625
Autor:
Li, Xiang, Yao, Yiqun, Jiang, Xin, Fang, Xuezhi, Wang, Chao, Liu, Xinzhang, Wang, Zihan, Zhao, Yu, Wang, Xin, Huang, Yuyao, Song, Shuangyong, Li, Yongxiang, Zhang, Zheng, Zhao, Bo, Sun, Aixin, Wang, Yequan, He, Zhongjiang, Wang, Zhongyuan, Li, Xuelong, Huang, Tiejun
Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence. As scaling laws underscore the potential of increasing model sizes, the academic community has intensified its investigations into LLMs with capacitie
Externí odkaz:
http://arxiv.org/abs/2407.02783
Autor:
Liang, Jiafeng, Jiang, Shixin, Wang, Zekun, Pan, Haojie, Chen, Zerui, Chu, Zheng, Liu, Ming, Fu, Ruiji, Wang, Zhongyuan, Qin, Bing
There are substantial instructional videos on the Internet, which provide us tutorials for completing various tasks. Existing instructional video datasets only focus on specific steps at the video level, lacking experiential guidelines at the task le
Externí odkaz:
http://arxiv.org/abs/2406.18227