Zobrazeno 1 - 10
of 9 662
pro vyhledávání: '"Yuan, Yi"'
Publikováno v:
Journal of Anhui Agricultural Sciences. 5/18/2024, Vol. 52 Issue 10, p11-14. 4p.
Autor:
Zhao, Junqi, Liu, Xubo, Zhao, Jinzheng, Yuan, Yi, Kong, Qiuqiang, Plumbley, Mark D., Wang, Wenwu
Universal sound separation (USS) is a task of separating mixtures of arbitrary sound sources. Typically, universal separation models are trained from scratch in a supervised manner, using labeled data. Self-supervised learning (SSL) is an emerging de
Externí odkaz:
http://arxiv.org/abs/2407.11745
Autor:
Yuan, Yi, Jia, Dongya, Zhuang, Xiaobin, Chen, Yuanzhe, Liu, Zhengxi, Chen, Zhuo, Wang, Yuping, Wang, Yuxuan, Liu, Xubo, Kang, Xiyuan, 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 simpli
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
Publikováno v:
岡山大学全学教育・学生支援機構教育研究紀要. 7:41-56
本文从概念化者(conceptualizer)的视点以及和认知对象的关系出发, 探讨领取表现“ 愿意”的使用条件。先行研究指出“ 愿意”的特性跟概念化者的意志选择有关。但我们发现 “ 愿意”在某些
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