Zobrazeno 1 - 10
of 19 697
pro vyhledávání: '"Xu Peng"'
Autor:
Zheng, Jiahao, Ren, Jinke, Xu, Peng, Yuan, Zhihao, Xu, Jie, Wang, Fangxin, Gui, Gui, Cui, Shuguang
Semantic communication is a promising technology to improve communication efficiency by transmitting only the semantic information of the source data. However, traditional semantic communication methods primarily focus on data reconstruction tasks, w
Externí odkaz:
http://arxiv.org/abs/2410.03459
Autor:
Law, Ka Nam Canaan, Yu, Mingshuo, Zhang, Lianglei, Zhang, Yiyi, Xu, Peng, Gao, Jerry, Liu, Jun
The quality control of printed circuit boards (PCBs) is paramount in advancing electronic device technology. While numerous machine learning methodologies have been utilized to augment defect detection efficiency and accuracy, previous studies have p
Externí odkaz:
http://arxiv.org/abs/2409.09555
Autor:
Liang, Bo, Guo, Hong, Zhao, Tianyu, wang, He, Evangelinelis, Herik, Xu, Yuxiang, liu, Chang, Liang, Manjia, Wei, Xiaotong, Yuan, Yong, Xu, Peng, Du, Minghui, Qian, Wei-Liang, Luo, Ziren
Extreme-mass-ratio inspiral (EMRI) signals pose significant challenges in gravitational wave (GW) astronomy owing to their low-frequency nature and highly complex waveforms, which occupy a high-dimensional parameter space with numerous variables. Giv
Externí odkaz:
http://arxiv.org/abs/2409.07957
Autor:
Liu, Lei-Yi-Nan, Yu, Shun-Yao, Peng, Shi-Rong, Sheng, Jie, Yi, Su, Xu, Peng, Gong, Shou-Shu, Shi, Tao, Cui, Jian
Rydberg atom array has been established as one appealing platform for quantum simulation and quantum computation. Recent experimental development of trapping and controlling two-species atoms using optical tweezer arrays has brought more complex inte
Externí odkaz:
http://arxiv.org/abs/2408.15965
Autor:
D'Ambrosio, David B., Abeyruwan, Saminda, Graesser, Laura, Iscen, Atil, Amor, Heni Ben, Bewley, Alex, Reed, Barney J., Reymann, Krista, Takayama, Leila, Tassa, Yuval, Choromanski, Krzysztof, Coumans, Erwin, Jain, Deepali, Jaitly, Navdeep, Jaques, Natasha, Kataoka, Satoshi, Kuang, Yuheng, Lazic, Nevena, Mahjourian, Reza, Moore, Sherry, Oslund, Kenneth, Shankar, Anish, Sindhwani, Vikas, Vanhoucke, Vincent, Vesom, Grace, Xu, Peng, Sanketi, Pannag R.
Achieving human-level speed and performance on real world tasks is a north star for the robotics research community. This work takes a step towards that goal and presents the first learned robot agent that reaches amateur human-level performance in c
Externí odkaz:
http://arxiv.org/abs/2408.03906
Autor:
Pan, Yue, Liu, Qile, Liu, Qing, Zhang, Li, Huang, Gan, Chen, Xin, Li, Fali, Xu, Peng, Liang, Zhen
Affective brain-computer interfaces (aBCIs) are increasingly recognized for their potential in monitoring and interpreting emotional states through electroencephalography (EEG) signals. Current EEG-based emotion recognition methods perform well with
Externí odkaz:
http://arxiv.org/abs/2407.20519
Autor:
Xu, Peng, Ping, Wei, Wu, Xianchao, Xu, Chejian, Liu, Zihan, Shoeybi, Mohammad, Catanzaro, Bryan
In this work, we introduce ChatQA 2, an Llama 3.0-based model with a 128K context window, designed to bridge the gap between open-source LLMs and leading proprietary models (e.g., GPT-4-Turbo) in long-context understanding and retrieval-augmented gen
Externí odkaz:
http://arxiv.org/abs/2407.14482
A self-consistent gravitational quantum field theory, with gravitational force treated on the same footing as the other three fundamental interactions, was established recently. The gravidynamics predicted by such a theory could lead to important imp
Externí odkaz:
http://arxiv.org/abs/2407.09410
Large language models (LLMs) are crucial in modern natural language processing and artificial intelligence. However, they face challenges in managing their significant memory requirements. Although quantization-aware training (QAT) offers a solution
Externí odkaz:
http://arxiv.org/abs/2407.11062
Autor:
Chiang, Hao-Tien Lewis, Xu, Zhuo, Fu, Zipeng, Jacob, Mithun George, Zhang, Tingnan, Lee, Tsang-Wei Edward, Yu, Wenhao, Schenck, Connor, Rendleman, David, Shah, Dhruv, Xia, Fei, Hsu, Jasmine, Hoech, Jonathan, Florence, Pete, Kirmani, Sean, Singh, Sumeet, Sindhwani, Vikas, Parada, Carolina, Finn, Chelsea, Xu, Peng, Levine, Sergey, Tan, Jie
An elusive goal in navigation research is to build an intelligent agent that can understand multimodal instructions including natural language and image, and perform useful navigation. To achieve this, we study a widely useful category of navigation
Externí odkaz:
http://arxiv.org/abs/2407.07775