Zobrazeno 1 - 10
of 27 107
pro vyhledávání: '"Li-Ya An"'
Autor:
Lei, Xiangli, Wu, Qingwen, Li, Hui, Li, Ya-Ping, Lei, Wei-Hua, Fan, Xiao, Wu, Jiancheng, Wang, Mengye, Yang, Weibo
The geometrically thick dusty torus structure is believed to exist in the nuclear region of galaxies (especially in active galactic nuclei, AGNs). The debris stream from a tidal disruption event (TDE) will possibly collide with the dusty torus and pr
Externí odkaz:
http://arxiv.org/abs/2410.20127
Autor:
Lian, Zheng, Sun, Haiyang, Sun, Licai, Chen, Lan, Chen, Haoyu, Gu, Hao, Wen, Zhuofan, Chen, Shun, Zhang, Siyuan, Yao, Hailiang, Xu, Mingyu, Chen, Kang, Liu, Bin, Liu, Rui, Liang, Shan, Li, Ya, Yi, Jiangyan, Tao, Jianhua
Multimodal Emotion Recognition (MER) is an important research topic. This paper advocates for a transformative paradigm in MER. The rationale behind our work is that current approaches often rely on a limited set of basic emotion labels, which do not
Externí odkaz:
http://arxiv.org/abs/2410.01495
The $CP$ violation (CPV) in the baryon system has not yet been definitively established. We demonstrate that individual partial-wave CPV in the $\Lambda_b\to p\pi^-,pK^-$ decays can exceed $10\%$, but the destruction between different partial waves r
Externí odkaz:
http://arxiv.org/abs/2409.02821
To address the limitation in multimodal emotion recognition (MER) performance arising from inter-modal information fusion, we propose a novel MER framework based on multitask learning where fusion occurs after alignment, called Foal-Net. The framewor
Externí odkaz:
http://arxiv.org/abs/2408.09438
Incremental object detection (IOD) aims to sequentially learn new classes, while maintaining the capability to locate and identify old ones. As the training data arrives with annotations only with new classes, IOD suffers from catastrophic forgetting
Externí odkaz:
http://arxiv.org/abs/2407.21687
Autor:
Fu, Ruibo, Liu, Rui, Qiang, Chunyu, Gao, Yingming, Lu, Yi, Shi, Shuchen, Wang, Tao, Li, Ya, Wen, Zhengqi, Zhang, Chen, Bu, Hui, Liu, Yukun, Qi, Xin, Li, Guanjun
The Inspirational and Convincing Audio Generation Challenge 2024 (ICAGC 2024) is part of the ISCSLP 2024 Competitions and Challenges track. While current text-to-speech (TTS) technology can generate high-quality audio, its ability to convey complex e
Externí odkaz:
http://arxiv.org/abs/2407.12038
Autor:
Li, Ya-Lun
Due to the rapid advancement of Large Language Model (LLM), the whole community eagerly consumes any available text data in order to train the LLM. Currently, large portion of the available text data are collected from internet, which has been though
Externí odkaz:
http://arxiv.org/abs/2406.13947
Migration commonly occurs during the epoch of planet formation. For emerging gas giant planets, it proceeds concurrently with their growth through the accretion of gas from their natal protoplanetary disks. Similar migration process should also be ap
Externí odkaz:
http://arxiv.org/abs/2406.12716
Diffusion-based singing voice conversion (SVC) models have shown better synthesis quality compared to traditional methods. However, in cross-domain SVC scenarios, where there is a significant disparity in pitch between the source and target voice dom
Externí odkaz:
http://arxiv.org/abs/2406.05692
Future Terahertz communications exhibit significant potential in accommodating ultra-high-rate services. Employing extremely large-scale array antennas is a key approach to realize this potential, as they can harness substantial beamforming gains to
Externí odkaz:
http://arxiv.org/abs/2406.05452