Zobrazeno 1 - 10
of 273
pro vyhledávání: '"Ma, Jinwen"'
Transformers have found extensive applications across various domains due to the powerful fitting capabilities. This success can be partially attributed to their inherent nonlinearity. Thus, in addition to the ReLU function employed in the original t
Externí odkaz:
http://arxiv.org/abs/2411.03884
Autor:
Deng, Jingyang, Shen, Zhengyang, Wang, Boyang, Su, Lixin, Cheng, Suqi, Nie, Ying, Wang, Junfeng, Yin, Dawei, Ma, Jinwen
The development of Long-Context Large Language Models (LLMs) has markedly advanced natural language processing by facilitating the process of textual data across long documents and multiple corpora. However, Long-Context LLMs still face two critical
Externí odkaz:
http://arxiv.org/abs/2410.06886
Autor:
Zhang, Zeren, Cheng, Jo-Ku, Deng, Jingyang, Tian, Lu, Ma, Jinwen, Qin, Ziran, Zhang, Xiaokai, Zhu, Na, Leng, Tuo
Mathematical reasoning remains an ongoing challenge for AI models, especially for geometry problems that require both linguistic and visual signals. As the vision encoders of most MLLMs are trained on natural scenes, they often struggle to understand
Externí odkaz:
http://arxiv.org/abs/2409.04214
Seismic fault detection holds significant geographical and practical application value, aiding experts in subsurface structure interpretation and resource exploration. Despite some progress made by automated methods based on deep learning, research i
Externí odkaz:
http://arxiv.org/abs/2407.14121
Combining face swapping with lip synchronization technology offers a cost-effective solution for customized talking face generation. However, directly cascading existing models together tends to introduce significant interference between tasks and re
Externí odkaz:
http://arxiv.org/abs/2405.05636
This paper introduces an approach to enhance seismic fault recognition through self-supervised pretraining. Seismic fault interpretation holds great significance in the fields of geophysics and geology. However, conventional methods for seismic fault
Externí odkaz:
http://arxiv.org/abs/2310.17974
Recently, a variety of methods under the name of non-contrastive learning (like BYOL, SimSiam, SwAV, DINO) show that when equipped with some asymmetric architectural designs, aligning positive pairs alone is sufficient to attain good performance in s
Externí odkaz:
http://arxiv.org/abs/2303.02387
Steerable models can provide very general and flexible equivariance by formulating equivariance requirements in the language of representation theory and feature fields, which has been recognized to be effective for many vision tasks. However, derivi
Externí odkaz:
http://arxiv.org/abs/2208.03720
Autor:
Li, Zonghui, Dong, Yongsheng, Shen, Longchao, Liu, Yafeng, Pei, Yuanhua, Yang, Haotian, Zheng, Lintao, Ma, Jinwen
Publikováno v:
In Neurocomputing 14 September 2024 598
Publikováno v:
In Pattern Recognition January 2025 157