Zobrazeno 1 - 10
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pro vyhledávání: '"Zhang, Yipeng"'
Autor:
Chen, Hong, Wang, Xin, Zhou, Yuwei, Huang, Bin, Zhang, Yipeng, Feng, Wei, Chen, Houlun, Zhang, Zeyang, Tang, Siao, Zhu, Wenwu
Multi-modal generative AI has received increasing attention in both academia and industry. Particularly, two dominant families of techniques are: i) The multi-modal large language model (MLLM) such as GPT-4V, which shows impressive ability for multi-
Externí odkaz:
http://arxiv.org/abs/2409.14993
The emergence of Large Language Models (LLMs) has revolutionized natural language processing in various applications especially in e-commerce. One crucial step before the application of such LLMs in these fields is to understand and compare the perfo
Externí odkaz:
http://arxiv.org/abs/2408.12779
Efficiently detecting target weld seams while ensuring sub-millimeter accuracy has always been an important challenge in autonomous welding, which has significant application in industrial practice. Previous works mostly focused on recognizing and lo
Externí odkaz:
http://arxiv.org/abs/2408.10710
Autor:
Zhang, Xiaoying, Peng, Baolin, Tian, Ye, Zhou, Jingyan, Zhang, Yipeng, Mi, Haitao, Meng, Helen
Large language models (LLMs) often struggle to provide up-to-date information due to their one-time training and the constantly evolving nature of the world. To keep LLMs current, existing approaches typically involve continued pre-training on new do
Externí odkaz:
http://arxiv.org/abs/2406.06326
Generating customized content in videos has received increasing attention recently. However, existing works primarily focus on customized text-to-video generation for single subject, suffering from subject-missing and attribute-binding problems when
Externí odkaz:
http://arxiv.org/abs/2405.12796
We formulate a unifying framework for unsupervised continual learning (UCL), which disentangles learning objectives that are specific to the present and the past data, encompassing stability, plasticity, and cross-task consolidation. The framework re
Externí odkaz:
http://arxiv.org/abs/2404.19132
Causal graph recovery is traditionally done using statistical estimation-based methods or based on individual's knowledge about variables of interests. They often suffer from data collection biases and limitations of individuals' knowledge. The advan
Externí odkaz:
http://arxiv.org/abs/2402.15301
Publikováno v:
Quantum Frontiers 2, 1 (2023)
Improving three-dimensional (3D) localization precision is of paramount importance for super-resolution imaging. By properly engineering the point spread function (PSF), such as utilizing Laguerre-Gaussian (LG) modes and their superposition, the ulti
Externí odkaz:
http://arxiv.org/abs/2312.11044
Customized text-to-video generation aims to generate text-guided videos with customized user-given subjects, which has gained increasing attention recently. However, existing works are primarily limited to generating videos for a single subject, leav
Externí odkaz:
http://arxiv.org/abs/2311.00990
Subject-driven text-to-image generation aims to generate customized images of the given subject based on the text descriptions, which has drawn increasing attention. Existing methods mainly resort to finetuning a pretrained generative model, where th
Externí odkaz:
http://arxiv.org/abs/2305.03374