Zobrazeno 1 - 10
of 21 327
pro vyhledávání: '"Large-Scale Evaluation"'
Accurate and reliable predictions of solar flares are essential due to their potentially significant impact on Earth and space-based infrastructure. Although deep learning models have shown notable predictive capabilities in this domain, current eval
Externí odkaz:
http://arxiv.org/abs/2411.18070
The goal for classification is to correctly assign labels to unseen samples. However, most methods misclassify samples with unseen labels and assign them to one of the known classes. Open-Set Classification (OSC) algorithms aim to maximize both close
Externí odkaz:
http://arxiv.org/abs/2406.09112
Monte Carlo methods, Variational Inference, and their combinations play a pivotal role in sampling from intractable probability distributions. However, current studies lack a unified evaluation framework, relying on disparate performance measures and
Externí odkaz:
http://arxiv.org/abs/2406.07423
Publikováno v:
Proc. Interspeech 2024, 4633-4637
The rapid growth of Speech Emotion Recognition (SER) has diverse global applications, from improving human-computer interactions to aiding mental health diagnostics. However, SER models might contain social bias toward gender, leading to unfair outco
Externí odkaz:
http://arxiv.org/abs/2406.05065
Autor:
Yang, Shu-wen, Chang, Heng-Jui, Huang, Zili, Liu, Andy T., Lai, Cheng-I, Wu, Haibin, Shi, Jiatong, Chang, Xuankai, Tsai, Hsiang-Sheng, Huang, Wen-Chin, Feng, Tzu-hsun, Chi, Po-Han, Lin, Yist Y., Chuang, Yung-Sung, Huang, Tzu-Hsien, Tseng, Wei-Cheng, Lakhotia, Kushal, Li, Shang-Wen, Mohamed, Abdelrahman, Watanabe, Shinji, Lee, Hung-yi
The foundation model paradigm leverages a shared foundation model to achieve state-of-the-art (SOTA) performance for various tasks, requiring minimal downstream-specific modeling and data annotation. This approach has proven crucial in the field of N
Externí odkaz:
http://arxiv.org/abs/2404.09385
Pretraining has been shown to improve performance in many domains, including semantic segmentation, especially in domains with limited labelled data. In this work, we perform a large-scale evaluation and benchmarking of various pretraining methods fo
Externí odkaz:
http://arxiv.org/abs/2402.17611
Autor:
Wu, Monica S.1 (AUTHOR) mwu@lyrahealth.com, Wickham, Robert E.2 (AUTHOR), Chen, Shih-Yin1 (AUTHOR), Varra, Alethea1 (AUTHOR), Chen, Connie1 (AUTHOR), Lungu, Anita1 (AUTHOR)
Publikováno v:
PLoS ONE. 11/8/2024, Vol. 19 Issue 11, p1-17. 17p.
Amidst the rapid evolution of LLMs, the significance of evaluation in comprehending and propelling these models forward is increasingly paramount. Evaluations have revealed that factors such as scaling, training types, architectures and other factors
Externí odkaz:
http://arxiv.org/abs/2403.15250
Autor:
Auld, Joshua, Cook, Jamie, Gurumurthy, Krishna Murthy, Khan, Nazmul, Mansour, Charbel, Rousseau, Aymeric, Sahin, Olcay, de Souza, Felipe, Verbas, Omer, Zuniga-Garcia, Natalia
Rapid technological progress and innovation in the areas of vehicle connectivity, automation and electrification, new modes of shared and alternative mobility, and advanced transportation system demand and supply management strategies, have motivated
Externí odkaz:
http://arxiv.org/abs/2403.14669
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