Zobrazeno 1 - 10
of 21 887
pro vyhledávání: '"An, Siwei"'
Meta-learning is a general approach to equip machine learning models with the ability to handle few-shot scenarios when dealing with many tasks. Most existing meta-learning methods work based on the assumption that all tasks are of equal importance.
Externí odkaz:
http://arxiv.org/abs/2410.18894
Autor:
Wu, Siwei, Peng, Zhongyuan, Du, Xinrun, Zheng, Tuney, Liu, Minghao, Wu, Jialong, Ma, Jiachen, Li, Yizhi, Yang, Jian, Zhou, Wangchunshu, Lin, Qunshu, Zhao, Junbo, Zhang, Zhaoxiang, Huang, Wenhao, Zhang, Ge, Lin, Chenghua, Liu, J. H.
Enabling Large Language Models (LLMs) to handle a wider range of complex tasks (e.g., coding, math) has drawn great attention from many researchers. As LLMs continue to evolve, merely increasing the number of model parameters yields diminishing perfo
Externí odkaz:
http://arxiv.org/abs/2410.13639
For decades, the Bj{\o}ntegaard Delta (BD) has been the metric for evaluating codec Rate-Distortion (R-D) performance. Yet, in most studies, BD is determined using just 4-5 R-D data points, could this be sufficient? As codecs and quality metrics adva
Externí odkaz:
http://arxiv.org/abs/2410.12220
Autor:
Xia, Peng, Han, Siwei, Qiu, Shi, Zhou, Yiyang, Wang, Zhaoyang, Zheng, Wenhao, Chen, Zhaorun, Cui, Chenhang, Ding, Mingyu, Li, Linjie, Wang, Lijuan, Yao, Huaxiu
Interleaved multimodal comprehension and generation, enabling models to produce and interpret both images and text in arbitrary sequences, have become a pivotal area in multimodal learning. Despite significant advancements, the evaluation of this cap
Externí odkaz:
http://arxiv.org/abs/2410.10139
Autor:
Xu, Jingyi, Tu, Siwei, Yang, Weidong, Li, Shuhao, Liu, Keyi, Luo, Yeqi, Ma, Lipeng, Fei, Ben, Bai, Lei
Variation of Arctic sea ice has significant impacts on polar ecosystems, transporting routes, coastal communities, and global climate. Tracing the change of sea ice at a finer scale is paramount for both operational applications and scientific studie
Externí odkaz:
http://arxiv.org/abs/2410.09111
Spiking Graph Networks (SGNs) have garnered significant attraction from both researchers and industry due to their ability to address energy consumption challenges in graph classification. However, SGNs are only effective for in-distribution data and
Externí odkaz:
http://arxiv.org/abs/2410.06883
Autor:
Gong, Junchao, Tu, Siwei, Yang, Weidong, Fei, Ben, Chen, Kun, Zhang, Wenlong, Yang, Xiaokang, Ouyang, Wanli, Bai, Lei
Precipitation nowcasting plays a pivotal role in socioeconomic sectors, especially in severe convective weather warnings. Although notable progress has been achieved by approaches mining the spatiotemporal correlations with deep learning, these metho
Externí odkaz:
http://arxiv.org/abs/2410.05805
Detecting deepfakes has become an important task. Most existing detection methods provide only real/fake predictions without offering human-comprehensible explanations. Recent studies leveraging MLLMs for deepfake detection have shown improvements in
Externí odkaz:
http://arxiv.org/abs/2410.06126
In StyleGAN, convolution kernels are shaped by both static parameters shared across images and dynamic modulation factors $w^+\in\mathcal{W}^+$ specific to each image. Therefore, $\mathcal{W}^+$ space is often used for image inversion and editing. Ho
Externí odkaz:
http://arxiv.org/abs/2410.06104
Autor:
Champagne, Jaclyn B., Wang, Feige, Yang, Jinyi, Fan, Xiaohui, Hennawi, Joseph F., Sun, Fengwu, Bañados, Eduardo, Bosman, Sarah E. I., Costa, Tiago, Habouzit, Melanie, Jin, Xiangyu, Jun, Hyunsung D., Li, Mingyu, Liu, Weizhe, Loiacono, Federica, Lupi, Alessandro, Mazzucchelli, Chiara, Pudoka, Maria, Rojas-Ruiz, Sofia, Tee, Wei Leong, Trebitsch, Maxime, Zhang, Haowen, Zhuang, Ming-Yang, Zou, Siwei
We present paper II comprising a 35 arcmin$^2$ JWST/NIRCam imaging and wide-field slitless spectroscopy mosaic centered on J0305$-$3150, a luminous quasar at $z=6.61$. The F356W grism data reveals 124 [OIII]+H$\beta$ emitters at $5.3
Externí odkaz:
http://arxiv.org/abs/2410.03827