Zobrazeno 1 - 10
of 3 589
pro vyhledávání: '"ZHANG, Mi"'
In recent years, text-to-image (T2I) generation models have made significant progress in generating high-quality images that align with text descriptions. However, these models also face the risk of unsafe generation, potentially producing harmful co
Externí odkaz:
http://arxiv.org/abs/2411.10329
Autor:
Xiong, Jing, Liu, Gongye, Huang, Lun, Wu, Chengyue, Wu, Taiqiang, Mu, Yao, Yao, Yuan, Shen, Hui, Wan, Zhongwei, Huang, Jinfa, Tao, Chaofan, Yan, Shen, Yao, Huaxiu, Kong, Lingpeng, Yang, Hongxia, Zhang, Mi, Sapiro, Guillermo, Luo, Jiebo, Luo, Ping, Wong, Ngai
Autoregressive modeling has been a huge success in the field of natural language processing (NLP). Recently, autoregressive models have emerged as a significant area of focus in computer vision, where they excel in producing high-quality visual conte
Externí odkaz:
http://arxiv.org/abs/2411.05902
Autor:
Siam, Shakhrul Iman, Ahn, Hyunho, Liu, Li, Alam, Samiul, Shen, Hui, Cao, Zhichao, Shroff, Ness, Krishnamachari, Bhaskar, Srivastava, Mani, Zhang, Mi
Publikováno v:
ACM Trans. Sen. Netw.(August 2024)
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we provide a systematic and comprehensive review of AIoT r
Externí odkaz:
http://arxiv.org/abs/2410.19998
Autor:
Shafter, Allen W., Zhao, Jingyuan, Hornoch, Kamil, Kučáková, Hana, Taguchi, Kenta, Zhang, Jiashuo, You, Jia, Wang, Binyu, Xu, Runwei, Wang, Weiye, Ren, Yuqing, Ding, Lanhe, Yan, Xiaochang, Zhang, Mi, Wang, Wei-Hao, Bond, Howard E., Williams, Robert, Zeimann, Gregory R.
We report the recent discovery of two new eruptions of the recurrent nova M31N 2017-01e in the Andromeda galaxy. The latest eruption, M31N 2024-08c, reached $R=17.8$ on 2024 August 06.85 UT, $\sim2$ months earlier than predicted. In addition to this
Externí odkaz:
http://arxiv.org/abs/2410.07105
Mamba and Vision Mamba (Vim) models have shown their potential as an alternative to methods based on Transformer architecture. This work introduces Fast Mamba for Vision (Famba-V), a cross-layer token fusion technique to enhance the training efficien
Externí odkaz:
http://arxiv.org/abs/2409.09808
Autor:
Wan, Zhongwei, Wu, Xinjian, Zhang, Yu, Xin, Yi, Tao, Chaofan, Zhu, Zhihong, Wang, Xin, Luo, Siqi, Xiong, Jing, Zhang, Mi
Efficient inference in Large Language Models (LLMs) is impeded by the growing memory demands of key-value (KV) caching, especially for longer sequences. Traditional KV cache eviction strategies, which prioritize less critical KV-pairs based on attent
Externí odkaz:
http://arxiv.org/abs/2406.13035
Autor:
Zhang, Tuo, Feng, Tiantian, Ni, Yibin, Cao, Mengqin, Liu, Ruying, Butler, Katharine, Weng, Yanjun, Zhang, Mi, Narayanan, Shrikanth S., Avestimehr, Salman
Large vision-language models (VLMs) have demonstrated remarkable abilities in understanding everyday content. However, their performance in the domain of art, particularly culturally rich art forms, remains less explored. As a pearl of human wisdom a
Externí odkaz:
http://arxiv.org/abs/2406.10318
Autor:
Liu, Che, Wan, Zhongwei, Wang, Yuqi, Shen, Hui, Wang, Haozhe, Zheng, Kangyu, Zhang, Mi, Arcucci, Rossella
Automatic radiology report generation can significantly benefit the labor-intensive process of report writing by radiologists, especially for 3D radiographs like CT scans, which are crucial for broad clinical diagnostics yet underexplored compared to
Externí odkaz:
http://arxiv.org/abs/2406.07146
Recent studies have noted an intriguing phenomenon termed Neural Collapse, that is, when the neural networks establish the right correlation between feature spaces and the training targets, their last-layer features, together with the classifier weig
Externí odkaz:
http://arxiv.org/abs/2405.05587
Image-text retrieval (ITR) plays a significant role in making informed decisions for various remote sensing (RS) applications. Nonetheless, creating ITR datasets containing vision and language modalities not only requires significant geo-spatial samp
Externí odkaz:
http://arxiv.org/abs/2403.10887