Zobrazeno 1 - 10
of 150
pro vyhledávání: '"Wang, Yuran"'
The generalization and performance of stereo matching networks are limited due to the domain gap of the existing synthetic datasets and the sparseness of GT labels in the real datasets. In contrast, monocular depth estimation has achieved significant
Externí odkaz:
http://arxiv.org/abs/2411.09151
Autor:
Hasegawa, Kimihiro, Imrattanatrai, Wiradee, Cheng, Zhi-Qi, Asada, Masaki, Holm, Susan, Wang, Yuran, Fukuda, Ken, Mitamura, Teruko
Multimodal systems have great potential to assist humans in procedural activities, where people follow instructions to achieve their goals. Despite diverse application scenarios, systems are typically evaluated on traditional classification tasks, e.
Externí odkaz:
http://arxiv.org/abs/2410.22211
Autor:
Li, Shuo, Ji, Tao, Fan, Xiaoran, Lu, Linsheng, Yang, Leyi, Yang, Yuming, Xi, Zhiheng, Zheng, Rui, Wang, Yuran, Zhao, Xiaohui, Gui, Tao, Zhang, Qi, Huang, Xuanjing
In the study of LLMs, sycophancy represents a prevalent hallucination that poses significant challenges to these models. Specifically, LLMs often fail to adhere to original correct responses, instead blindly agreeing with users' opinions, even when t
Externí odkaz:
http://arxiv.org/abs/2410.11302
In the realm of medical image analysis, self-supervised learning (SSL) techniques have emerged to alleviate labeling demands, while still facing the challenge of training data scarcity owing to escalating resource requirements and privacy constraints
Externí odkaz:
http://arxiv.org/abs/2409.20332
Autor:
Yang, Yuming, Zhao, Wantong, Huang, Caishuang, Ye, Junjie, Wang, Xiao, Zheng, Huiyuan, Nan, Yang, Wang, Yuran, Xu, Xueying, Huang, Kaixin, Zhang, Yunke, Gui, Tao, Zhang, Qi, Huang, Xuanjing
Open Named Entity Recognition (NER), which involves identifying arbitrary types of entities from arbitrary domains, remains challenging for Large Language Models (LLMs). Recent studies suggest that fine-tuning LLMs on extensive NER data can boost the
Externí odkaz:
http://arxiv.org/abs/2406.11192
The rapid development of 3D acquisition technology has made it possible to obtain point clouds of real-world terrains. However, due to limitations in sensor acquisition technology or specific requirements, point clouds often contain defects such as h
Externí odkaz:
http://arxiv.org/abs/2404.03572
Coreset selection seeks to choose a subset of crucial training samples for efficient learning. It has gained traction in deep learning, particularly with the surge in training dataset sizes. Sample selection hinges on two main aspects: a sample's rep
Externí odkaz:
http://arxiv.org/abs/2401.16193
Autor:
Wang, Yuran1 (AUTHOR), Dai, Wei1 (AUTHOR), Wu, Tian1 (AUTHOR), Qi, Hongyan1 (AUTHOR), Tao, Junhui1 (AUTHOR), Wang, Chuanhui1 (AUTHOR), Li, Jie1 (AUTHOR), Cao, Xiuying1 (AUTHOR), Liu, Liangpeng1 (AUTHOR), Fang, Liuyi1 (AUTHOR), Wang, Chun1 (AUTHOR), Gong, Nengyuan1 (AUTHOR), Liu, Yuxuan1 (AUTHOR), Chen, Xinqi1,2,3 (AUTHOR) chenxinqi@hue.edu.com, Jiang, Wan2 (AUTHOR) wanjiang@dhu.edu.cn, Wang, Xiaolin3 (AUTHOR) xiaolin@uow.edu.au
Publikováno v:
Small Science. Nov2024, Vol. 4 Issue 11, p1-17. 17p.
Publikováno v:
In Plant Physiology and Biochemistry September 2024 214
Publikováno v:
In Materials & Design May 2024 241