Zobrazeno 1 - 10
of 567
pro vyhledávání: '"HU Dou"'
Driving safety and responsibility determination are indispensable pieces of the puzzle for autonomous driving. They are also deeply related to the allocation of right-of-way and the determination of accident liability. Therefore, Intel/Mobileye desig
Externí odkaz:
http://arxiv.org/abs/2409.02503
Many fake news detection studies have achieved promising performance by extracting effective semantic and structure features from both content and propagation trees. However, it is challenging to apply them to practical situations, especially when us
Externí odkaz:
http://arxiv.org/abs/2407.09894
This paper proposes an information-theoretic representation learning framework, named conditional information flow maximization, to extract noise-invariant sufficient representations for the input data and target task. It promotes the learned represe
Externí odkaz:
http://arxiv.org/abs/2406.05510
This paper presents a new supervised representation learning framework, namely structured probabilistic coding (SPC), to learn compact and informative representations from input related to the target task. SPC is an encoder-only probabilistic coding
Externí odkaz:
http://arxiv.org/abs/2312.13933
Autor:
Zhichao Pan, Xing Huang, Yunlong Fan, Shaoze Wang, Yiyu Liu, Xuzhong Cong, Tingsong Zhang, Shichao Qi, Ying Xing, Yu-Qing Zheng, Jian Li, Xiaoming Zhang, Wei Xu, Lei Sun, Jian Wang, Jin-Hu Dou
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024)
Abstract Two-dimensional conjugated coordination polymers exhibit remarkable charge transport properties, with copper-based benzenehexathiol (Cu-BHT) being a rare superconductor. However, the atomic structure of Cu-BHT has remained unresolved, hinder
Externí odkaz:
https://doaj.org/article/1dc7476d68604e66b89f8cea50ebf7cf
Extracting generalized and robust representations is a major challenge in emotion recognition in conversations (ERC). To address this, we propose a supervised adversarial contrastive learning (SACL) framework for learning class-spread structured repr
Externí odkaz:
http://arxiv.org/abs/2306.01505
This paper describes our system designed for SemEval-2023 Task 12: Sentiment analysis for African languages. The challenge faced by this task is the scarcity of labeled data and linguistic resources in low-resource settings. To alleviate these, we pr
Externí odkaz:
http://arxiv.org/abs/2306.01093
Pre-trained language models have achieved promising performance on general benchmarks, but underperform when migrated to a specific domain. Recent works perform pre-training from scratch or continual pre-training on domain corpora. However, in many s
Externí odkaz:
http://arxiv.org/abs/2211.00430
Publikováno v:
In Journal of Alloys and Compounds 25 October 2024 1003
Publikováno v:
In Ceramics International 15 October 2024 50(20) Part A:37820-37832