Zobrazeno 1 - 10
of 19 766
pro vyhledávání: '"An, Yuyan"'
Deep neural networks perform well in object recognition, but do they perceive objects like humans? This study investigates the Gestalt principle of closure in convolutional neural networks. We propose a protocol to identify closure and conduct experi
Externí odkaz:
http://arxiv.org/abs/2411.00627
Molecular generation and molecular property prediction are both crucial for drug discovery, but they are often developed independently. Inspired by recent studies, which demonstrate that diffusion model, a prominent generative approach, can learn mea
Externí odkaz:
http://arxiv.org/abs/2410.10516
In recent years, the rapid evolution of satellite communications play a pivotal role in addressing the ever-increasing demand for global connectivity, among which the Low Earth Orbit (LEO) satellites attract a great amount of attention due to their l
Externí odkaz:
http://arxiv.org/abs/2409.17553
Autor:
Chen, Yuyan, Qian, Yiwen, Yan, Songzhou, Jia, Jiyuan, Li, Zhixu, Xiao, Yanghua, Li, Xiaobo, Yang, Ming, Guo, Qingpei
In the era of social media video platforms, popular ``hot-comments'' play a crucial role in attracting user impressions of short-form videos, making them vital for marketing and branding purpose. However, existing research predominantly focuses on ge
Externí odkaz:
http://arxiv.org/abs/2409.15196
Autor:
Chen, Yuyan, Yu, Tianhao, Li, Yueze, Yan, Songzhou, Liu, Sijia, Liang, Jiaqing, Xiao, Yanghua
The evaluation of the problem-solving capability under incomplete information scenarios of Large Language Models (LLMs) is increasingly important, encompassing capabilities such as questioning, knowledge search, error detection, and path planning. Cu
Externí odkaz:
http://arxiv.org/abs/2409.14762
Emotional intelligence in large language models (LLMs) is of great importance in Natural Language Processing. However, the previous research mainly focus on basic sentiment analysis tasks, such as emotion recognition, which is not enough to evaluate
Externí odkaz:
http://arxiv.org/abs/2409.13359
Autor:
Chen, Yuyan, Xiao, Yanghua
Emotion cognition in large language models (LLMs) is crucial for enhancing performance across various applications, such as social media, human-computer interaction, and mental health assessment. We explore the current landscape of research, which pr
Externí odkaz:
http://arxiv.org/abs/2409.13354
Autor:
Chen, Dingshuo, Li, Zhixun, Ni, Yuyan, Zhang, Guibin, Wang, Ding, Liu, Qiang, Wu, Shu, Yu, Jeffrey Xu, Wang, Liang
With the emergence of various molecular tasks and massive datasets, how to perform efficient training has become an urgent yet under-explored issue in the area. Data pruning (DP), as an oft-stated approach to saving training burdens, filters out less
Externí odkaz:
http://arxiv.org/abs/2409.01081
The human brain has an inherent ability to fill in gaps to perceive figures as complete wholes, even when parts are missing or fragmented. This phenomenon is known as Closure in psychology, one of the Gestalt laws of perceptual organization, explaini
Externí odkaz:
http://arxiv.org/abs/2408.12460
Dr.Academy: A Benchmark for Evaluating Questioning Capability in Education for Large Language Models
Teachers are important to imparting knowledge and guiding learners, and the role of large language models (LLMs) as potential educators is emerging as an important area of study. Recognizing LLMs' capability to generate educational content can lead t
Externí odkaz:
http://arxiv.org/abs/2408.10947