Zobrazeno 1 - 10
of 6 192
pro vyhledávání: '"Yuan, Yi"'
Autor:
Yuan, Yi, Jia, Dongya, Zhuang, Xiaobin, Chen, Yuanzhe, Liu, Zhengxi, Chen, Zhuo, Wang, Yuping, Wang, Yuxuan, Liu, Xubo, Plumbley, Mark D., Wang, Wenwu
Generative models have shown significant achievements in audio generation tasks. However, existing models struggle with complex and detailed prompts, leading to potential performance degradation. We hypothesize that this problem stems from the low qu
Externí odkaz:
http://arxiv.org/abs/2407.04416
Topology optimization (TO) is a powerful method to design innovative structures with improved heat transfer performance. In the present study, a multi-fidelity TO method with a delicately defined objective function is developed for flow boiling heat
Externí odkaz:
http://arxiv.org/abs/2405.13519
Large language models (LLMs) have significantly advanced audio processing through audio codecs that convert audio into discrete tokens, enabling the application of language modelling techniques to audio data. However, traditional codecs often operate
Externí odkaz:
http://arxiv.org/abs/2405.00233
Autor:
Yuan, Yi, Chen, Zhuo, Liu, Xubo, Liu, Haohe, Xu, Xuenan, Jia, Dongya, Chen, Yuanzhe, Plumbley, Mark D., Wang, Wenwu
Contrastive language-audio pretraining~(CLAP) has been developed to align the representations of audio and language, achieving remarkable performance in retrieval and classification tasks. However, current CLAP struggles to capture temporal informati
Externí odkaz:
http://arxiv.org/abs/2404.17806
Non-line-of-sight localization in signal-deprived environments is a challenging yet pertinent problem. Acoustic methods in such predominantly indoor scenarios encounter difficulty due to the reverberant nature. In this study, we aim to locate sound s
Externí odkaz:
http://arxiv.org/abs/2404.01611
Autor:
Li, Ang, Xiao, Qiugen, Cao, Peng, Tang, Jian, Yuan, Yi, Zhao, Zijie, Chen, Xiaoyuan, Zhang, Liang, Li, Xiangyang, Yang, Kaitong, Guo, Weidong, Gan, Yukang, Yu, Xu, Wang, Daniell, Shan, Ying
Reinforcement Learning from AI Feedback (RLAIF) has the advantages of shorter annotation cycles and lower costs over Reinforcement Learning from Human Feedback (RLHF), making it highly efficient during the rapid strategy iteration periods of large la
Externí odkaz:
http://arxiv.org/abs/2403.08309
This paper proposes a novel three-dimensional (3D) theoretical regular-shaped geometry-based stochastic model (RS-GBSM) and the corresponding sum-of-sinusoids (SoS) simulation model for non-isotropic multiple-input multiple-output (MIMO) vehicle-to-v
Externí odkaz:
http://arxiv.org/abs/2312.00550
Recent works based on convolutional encoder-decoder architecture and 3DMM parameterization have shown great potential for canonical view reconstruction from a single input image. Conventional CNN architectures benefit from exploiting the spatial corr
Externí odkaz:
http://arxiv.org/abs/2310.14237
Autor:
Yuan, Yi, Cui, Kaifeng, Liu, Daoxin, Yuan, Jinbo, Cao, Jian, Wang, Dehao, Chao, Sijia, Shu, Hualin, Haung, Xueren
Optical clock network requires the establishment of optical frequency transmission link between multiple optical clocks, utilizing narrow linewidth lasers. Despite achieving link noise levels of 10${^{-20}}$, the final accuracy is limited by the phas
Externí odkaz:
http://arxiv.org/abs/2310.08835
Despite recent progress in text-to-audio (TTA) generation, we show that the state-of-the-art models, such as AudioLDM, trained on datasets with an imbalanced class distribution, such as AudioCaps, are biased in their generation performance. Specifica
Externí odkaz:
http://arxiv.org/abs/2309.08051