Zobrazeno 1 - 10
of 233 178
pro vyhledávání: '"Hsieh OF"'
Flying quadrotors in tight formations is a challenging problem. It is known that in the near-field airflow of a quadrotor, the aerodynamic effects induced by the propellers are complex and difficult to characterize. Although machine learning tools ca
Externí odkaz:
http://arxiv.org/abs/2410.09727
Autor:
Wang, Tianyang, Bi, Ziqian, Zhang, Yichao, Liu, Ming, Hsieh, Weiche, Feng, Pohsun, Yan, Lawrence K. Q., Wen, Yizhu, Peng, Benji, Liu, Junyu, Chen, Keyu, Zhang, Sen, Li, Ming, Jiang, Chuanqi, Song, Xinyuan, Yang, Junjie, Jing, Bowen, Ren, Jintao, Song, Junhao, Tseng, Hong-Ming, Chen, Silin, Wang, Yunze, Liang, Chia Xin, Xu, Jiawei, Pan, Xuanhe, Wang, Jinlang, Niu, Qian
Deep learning has transformed AI applications but faces critical security challenges, including adversarial attacks, data poisoning, model theft, and privacy leakage. This survey examines these vulnerabilities, detailing their mechanisms and impact o
Externí odkaz:
http://arxiv.org/abs/2412.08969
Autor:
Seligman, Darryl Z., Farnocchia, Davide, Micheli, Marco, Hainaut, Olivier R., Hsieh, Henry H., Feinstein, Adina D., Chesley, Steven R., Taylor, Aster G., Masiero, Joseph, Meech, Karen J.
Publikováno v:
Proc. Natl. Acad. Sci., 121, 2024
Small bodies are capable of delivering essential prerequisites for the development of life, such as volatiles and organics, to the terrestrial planets. For example, empirical evidence suggests that water was delivered to the Earth by hydrated planete
Externí odkaz:
http://arxiv.org/abs/2412.07603
In the peer review process of top-tier machine learning (ML) and artificial intelligence (AI) conferences, reviewers are assigned to papers through automated methods. These assignment algorithms consider two main factors: (1) reviewers' expressed int
Externí odkaz:
http://arxiv.org/abs/2412.06606
Autor:
Liu, Zhijian, Zhu, Ligeng, Shi, Baifeng, Zhang, Zhuoyang, Lou, Yuming, Yang, Shang, Xi, Haocheng, Cao, Shiyi, Gu, Yuxian, Li, Dacheng, Li, Xiuyu, Fang, Yunhao, Chen, Yukang, Hsieh, Cheng-Yu, Huang, De-An, Cheng, An-Chieh, Nath, Vishwesh, Hu, Jinyi, Liu, Sifei, Krishna, Ranjay, Xu, Daguang, Wang, Xiaolong, Molchanov, Pavlo, Kautz, Jan, Yin, Hongxu, Han, Song, Lu, Yao
Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention. This paper introduces NVILA, a family of open VLMs designed to optimize both efficiency and accuracy
Externí odkaz:
http://arxiv.org/abs/2412.04468
In the game development process, creating character animations is a vital step that involves several stages. Typically for 2D games, illustrators begin by designing the main character image, which serves as the foundation for all subsequent animation
Externí odkaz:
http://arxiv.org/abs/2412.03685
Autor:
Bigverdi, Mahtab, Luo, Zelun, Hsieh, Cheng-Yu, Shen, Ethan, Chen, Dongping, Shapiro, Linda G., Krishna, Ranjay
Multimodal language models (MLMs) still face challenges in fundamental visual perception tasks where specialized models excel. Tasks requiring reasoning about 3D structures benefit from depth estimation, and reasoning about 2D object instances benefi
Externí odkaz:
http://arxiv.org/abs/2412.03548
In recent years, many neural network (NN) verifiers have been developed to formally verify certain properties of neural networks such as robustness. Although many benchmarks have been constructed to evaluate the performance of NN verifiers, they typi
Externí odkaz:
http://arxiv.org/abs/2412.03154
Autor:
Hsieh, Weiche, Bi, Ziqian, Chen, Keyu, Peng, Benji, Zhang, Sen, Xu, Jiawei, Wang, Jinlang, Yin, Caitlyn Heqi, Zhang, Yichao, Feng, Pohsun, Wen, Yizhu, Wang, Tianyang, Li, Ming, Liang, Chia Xin, Ren, Jintao, Niu, Qian, Chen, Silin, Yan, Lawrence K. Q., Xu, Han, Tseng, Hong-Ming, Song, Xinyuan, Jing, Bowen, Yang, Junjie, Song, Junhao, Liu, Junyu, Liu, Ming
Advancements in artificial intelligence, machine learning, and deep learning have catalyzed the transformation of big data analytics and management into pivotal domains for research and application. This work explores the theoretical foundations, met
Externí odkaz:
http://arxiv.org/abs/2412.02187
Autor:
Hsieh, Jane, Zhang, Angie, Rasetarinera, Mialy, Chou, Erik, Ngo, Daniel, Lightman, Karen, Lee, Min Kyung, Zhu, Haiyi
The proliferating adoption of platform-based gig work increasingly raises concerns for worker conditions. Past studies documented how platforms leveraged design to exploit labor, withheld information to generate power asymmetries, and left workers al
Externí odkaz:
http://arxiv.org/abs/2412.02973