Zobrazeno 1 - 10
of 301
pro vyhledávání: '"Wu, Yushu"'
Autor:
Zhan, Zheng, Wu, Yushu, Gong, Yifan, Meng, Zichong, Kong, Zhenglun, Yang, Changdi, Yuan, Geng, Zhao, Pu, Niu, Wei, Wang, Yanzhi
The rapid progress in artificial intelligence-generated content (AIGC), especially with diffusion models, has significantly advanced development of high-quality video generation. However, current video diffusion models exhibit demanding computational
Externí odkaz:
http://arxiv.org/abs/2411.01171
Autor:
Zhan, Zheng, Wu, Yushu, Kong, Zhenglun, Yang, Changdi, Gong, Yifan, Shen, Xuan, Lin, Xue, Zhao, Pu, Wang, Yanzhi
Recent advancements in State Space Models (SSMs) have attracted significant interest, particularly in models optimized for parallel training and handling long-range dependencies. Architectures like Mamba have scaled to billions of parameters with sel
Externí odkaz:
http://arxiv.org/abs/2410.14725
Autor:
Gong, Yifan, Wu, Yushu, Zhan, Zheng, Zhao, Pu, Liu, Liangkai, Wu, Chao, Tang, Xulong, Wang, Yanzhi
Two-stage object detectors exhibit high accuracy and precise localization, especially for identifying small objects that are favorable for various edge applications. However, the high computation costs associated with two-stage detection methods caus
Externí odkaz:
http://arxiv.org/abs/2410.10847
Autor:
Zhan, Zheng, Kong, Zhenglun, Gong, Yifan, Wu, Yushu, Meng, Zichong, Zheng, Hangyu, Shen, Xuan, Ioannidis, Stratis, Niu, Wei, Zhao, Pu, Wang, Yanzhi
State Space Models (SSMs) have the advantage of keeping linear computational complexity compared to attention modules in transformers, and have been applied to vision tasks as a new type of powerful vision foundation model. Inspired by the observatio
Externí odkaz:
http://arxiv.org/abs/2409.18962
Autor:
Shen, Xuan, Zhao, Pu, Gong, Yifan, Kong, Zhenglun, Zhan, Zheng, Wu, Yushu, Lin, Ming, Wu, Chao, Lin, Xue, Wang, Yanzhi
Large Language Models (LLMs) have long held sway in the realms of artificial intelligence research. Numerous efficient techniques, including weight pruning, quantization, and distillation, have been embraced to compress LLMs, targeting memory reducti
Externí odkaz:
http://arxiv.org/abs/2409.17372
Autor:
Rupprecht, Timothy, Chang, Sung-En, Wu, Yushu, Lu, Lei, Nan, Enfu, Li, Chih-hsiang, Lai, Caiyue, Li, Zhimin, Hu, Zhijun, He, Yumei, Kaeli, David, Wang, Yanzhi
Publikováno v:
2024 Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence Demo Track. Pages 8780-8783
We present a novel prompting strategy for artificial intelligence driven digital avatars. To better quantify how our prompting strategy affects anthropomorphic features like humor, authenticity, and favorability we present Crowd Vote - an adaptation
Externí odkaz:
http://arxiv.org/abs/2408.04068
Autor:
Wu, Chao, Gong, Yifan, Liu, Liangkai, Li, Mengquan, Wu, Yushu, Shen, Xuan, Li, Zhimin, Yuan, Geng, Shi, Weisong, Wang, Yanzhi
Object detection on the edge (Edge-OD) is in growing demand thanks to its ever-broad application prospects. However, the development of this field is rigorously restricted by the deployment dilemma of simultaneously achieving high accuracy, excellent
Externí odkaz:
http://arxiv.org/abs/2408.05363
Autor:
Zhang, Zhixing, Li, Yanyu, Wu, Yushu, Xu, Yanwu, Kag, Anil, Skorokhodov, Ivan, Menapace, Willi, Siarohin, Aliaksandr, Cao, Junli, Metaxas, Dimitris, Tulyakov, Sergey, Ren, Jian
Diffusion-based video generation models have demonstrated remarkable success in obtaining high-fidelity videos through the iterative denoising process. However, these models require multiple denoising steps during sampling, resulting in high computat
Externí odkaz:
http://arxiv.org/abs/2406.04324
If our noise-canceling headphones can understand our audio environments, they can then inform us of important sound events, tune equalization based on the types of content we listen to, and dynamically adjust noise cancellation parameters based on au
Externí odkaz:
http://arxiv.org/abs/2404.04386