Zobrazeno 1 - 10
of 2 623
pro vyhledávání: '"Gu, Yue"'
Autor:
Metere, Roberto, Ye, Kangfeng, Gu, Yue, Zhang, Zhi, Alrajeh, Dalal, Sevegnani, Michele, Yadav, Poonam
As Open Radio Access Networks (O-RAN) continue to expand, AI-driven applications (xApps) are increasingly being deployed enhance network management. However, developing xApps without formal verification risks introducing logical inconsistencies, part
Externí odkaz:
http://arxiv.org/abs/2411.03943
Autor:
Zhang, Jia, Qi, Peng, Xiao, Li, Yuan, Mengxi, Chuan, Jun, Zeng, Yaling, Lin, Li-mei, Gu, Yue, Zhang, Yan, Liao, Duan-fang, Li, Kai
Sensitive and reliable methylation assay is important for oncogentic studies and clinical applications. Here, a new methylation assay was developed by the use of adapter-dependent adapter in library preparation. This new assay avoids the use of bisul
Externí odkaz:
http://arxiv.org/abs/2410.04137
Autor:
Zhang, Jiayi, Sun, Chenxin, Gu, Yue, Zhang, Qingyu, Lin, Jiayi, Du, Xiaojiang, Qian, Chenxiong
The gaming industry has experienced substantial growth, but cheating in online games poses a significant threat to the integrity of the gaming experience. Cheating, particularly in first-person shooter (FPS) games, can lead to substantial losses for
Externí odkaz:
http://arxiv.org/abs/2409.14830
Autor:
Du, Zhihao, Chen, Qian, Zhang, Shiliang, Hu, Kai, Lu, Heng, Yang, Yexin, Hu, Hangrui, Zheng, Siqi, Gu, Yue, Ma, Ziyang, Gao, Zhifu, Yan, Zhijie
Recent years have witnessed a trend that large language model (LLM) based text-to-speech (TTS) emerges into the mainstream due to their high naturalness and zero-shot capacity. In this paradigm, speech signals are discretized into token sequences, wh
Externí odkaz:
http://arxiv.org/abs/2407.05407
Autor:
An, Keyu, Chen, Qian, Deng, Chong, Du, Zhihao, Gao, Changfeng, Gao, Zhifu, Gu, Yue, He, Ting, Hu, Hangrui, Hu, Kai, Ji, Shengpeng, Li, Yabin, Li, Zerui, Lu, Heng, Luo, Haoneng, Lv, Xiang, Ma, Bin, Ma, Ziyang, Ni, Chongjia, Song, Changhe, Shi, Jiaqi, Shi, Xian, Wang, Hao, Wang, Wen, Wang, Yuxuan, Xiao, Zhangyu, Yan, Zhijie, Yang, Yexin, Zhang, Bin, Zhang, Qinglin, Zhang, Shiliang, Zhao, Nan, Zheng, Siqi
This report introduces FunAudioLLM, a model family designed to enhance natural voice interactions between humans and large language models (LLMs). At its core are two innovative models: SenseVoice, which handles multilingual speech recognition, emoti
Externí odkaz:
http://arxiv.org/abs/2407.04051
Autor:
Liu, Qiye, Su, Wenjie, Gu, Yue, Zhang, Xi, Xia, Xiuquan, Wang, Le, Xiao, Ke, Cui, Xiaodong, Zou, Xiaolong, Xi, Bin, Mei, Jia-Wei, Dai, Jun-Feng
Interlayer magnetic interactions play a pivotal role in determining the magnetic arrangement within van der Waals (vdW) magnets, and the remarkable tunability of these interactions through applied pressure further enhances their significance. Here, w
Externí odkaz:
http://arxiv.org/abs/2404.09569
Autor:
Abioye, Ayodeji O., Hunt, William, Gu, Yue, Schneiders, Eike, Naiseh, Mohammad, Fischer, Joel E., Ramchurn, Sarvapali D., Soorati, Mohammad D., Archibald, Blair, Sevegnani, Michele
Formal Modelling is often used as part of the design and testing process of software development to ensure that components operate within suitable bounds even in unexpected circumstances. In this paper, we use predictive formal modelling (PFM) at run
Externí odkaz:
http://arxiv.org/abs/2401.11945
In supervised speech separation, permutation invariant training (PIT) is widely used to handle label ambiguity by selecting the best permutation to update the model. Despite its success, previous studies showed that PIT is plagued by excessive label
Externí odkaz:
http://arxiv.org/abs/2311.12199
Publikováno v:
Xin yixue, Vol 55, Iss 10, Pp 779-786 (2024)
Objective To evaluate the diagnostic value of total serum immunoglobulin E （IgE） levels， eosinophil （EOS） count and percentage in the diagnosis of allergic rhinitis （AR）， and to construct a diagnostic model for preliminary diagnosis o
Externí odkaz:
https://doaj.org/article/52580cb6529e4c26a24a14632fd86d05
Large self-supervised models are effective feature extractors, but their application is challenging under on-device budget constraints and biased dataset collection, especially in keyword spotting. To address this, we proposed a knowledge distillatio
Externí odkaz:
http://arxiv.org/abs/2307.02720