Zobrazeno 1 - 10
of 12 804
pro vyhledávání: '"An, Yunhe"'
Large Language Models (LLMs) have shown remarkable abilities across various language tasks, but solving complex reasoning problems remains a challenge. While existing methods like Chain-of-Thought (CoT) and Tree-of-Thought (ToT) enhance reasoning by
Externí odkaz:
http://arxiv.org/abs/2412.09078
Publikováno v:
ACMSE '24: Proceedings of the 2024 ACM Southeast Conference
Mathematics education, a crucial and basic field, significantly influences students' learning in related subjects and their future careers. Utilizing artificial intelligence to interpret and comprehend math problems in education is not yet fully expl
Externí odkaz:
http://arxiv.org/abs/2412.08633
The rapid growth of academic publications has exacerbated the issue of author name ambiguity in online digital libraries. Despite advances in name disambiguation algorithms, cumulative errors continue to undermine the reliability of academic systems.
Externí odkaz:
http://arxiv.org/abs/2412.03930
Autor:
Zhou, Hang, Tang, Yehui, Qin, Haochen, Yang, Yujie, Jin, Renren, Xiong, Deyi, Han, Kai, Wang, Yunhe
The efficacy of large language models (LLMs) on downstream tasks usually hinges on instruction tuning, which relies critically on the quality of training data. Unfortunately, collecting high-quality and diverse data is both expensive and time-consumi
Externí odkaz:
http://arxiv.org/abs/2411.14497
Publikováno v:
Proc. INTERSPEECH 2023, 226-230
Recurrent neural network (RNNs) that are capable of modeling long-distance dependencies are widely used in various speech tasks, eg., keyword spotting (KWS) and speech enhancement (SE). Due to the limitation of power and memory in low-resource device
Externí odkaz:
http://arxiv.org/abs/2411.14489
Autor:
Ding, Ning, Tang, Yehui, Qin, Haochen, Zhou, Zhenli, Xu, Chao, Li, Lin, Han, Kai, Liao, Heng, Wang, Yunhe
In order to reduce the computational complexity of large language models, great efforts have been made to to improve the efficiency of transformer models such as linear attention and flash-attention. However, the model size and corresponding computat
Externí odkaz:
http://arxiv.org/abs/2411.12992
Autor:
Zhao, Liang, Geng, Shenglin, Tang, Xiongyan, Hawbani, Ammar, Sun, Yunhe, Xu, Lexi, Tarchi, Daniele
Low Earth Orbit (LEO) satellite constellations have seen significant growth and functional enhancement in recent years, which integrates various capabilities like communication, navigation, and remote sensing. However, the heterogeneity of data colle
Externí odkaz:
http://arxiv.org/abs/2411.07752
A Koszul duality-type correspondence between coderived categories of conilpotent differential graded Lie coalgebras and their Chevalley-Eilenberg differential graded algebras is established. This gives an interpretation of Lie coalgebra cohomology as
Externí odkaz:
http://arxiv.org/abs/2411.02884
In this paper, we give the necessary and sufficient conditions of the integrability of relative Rota-Baxter Lie algebras via double Lie groups, matched pairs of Lie groups and factorization of diffeomorphisms respectively. We use the integrability of
Externí odkaz:
http://arxiv.org/abs/2410.23547
With the rapid advancement of autonomous driving technology, efficient and accurate object detection capabilities have become crucial factors in ensuring the safety and reliability of autonomous driving systems. However, in low-visibility environment
Externí odkaz:
http://arxiv.org/abs/2410.17734