Zobrazeno 1 - 10
of 17 860
pro vyhledávání: '"Boyang An"'
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11176 (2023)
Providing interpretable explanations can notably enhance users’ confidence and satisfaction with regard to recommender systems. Counterfactual explanations demonstrate remarkable performance in the realm of explainable sequential recommendation. Ho
Externí odkaz:
https://doaj.org/article/02db58046657425fb76cdd45004affe2
Autor:
Wulff, Arne, Venkata, Swapan Madabhushi, Chen, Boyang, Feld, Sebastian, Möller, Matthias, Tang, Yinglu
We, the QAIMS lab lab at the Aerospace Faculty of TU Delft, participated as finalists in the Airbus/BMW Quantum Computing Challenge 2024. Stacking sequence retrieval, a complex combinatorial task within a bi-level optimization framework, is crucial f
Externí odkaz:
http://arxiv.org/abs/2411.10303
Understanding algorithmic error accumulation in quantum simulation is crucial due to its fundamental significance and practical applications in simulating quantum many-body system dynamics. Conventional theories typically apply the triangle inequalit
Externí odkaz:
http://arxiv.org/abs/2411.03255
Autor:
Huang, Shenyang, Yu, Boyang, Ma, Yixuan, Pan, Chenghao, Ma, Junwei, Zhou, Yuxuan, Ma, Yaozhenghang, Yang, Ke, Wu, Hua, Lei, Yuchen, Xing, Qiaoxia, Mu, Lei, Zhang, Jiasheng, Mou, Yanlin, Yan, Hugen
Publikováno v:
Science386,526-531(2024)
Bright dipolar excitons, which contain electrical dipoles and have high oscillator strength, are an ideal platform for studying correlated quantum phenomena. They usually rely on carrier tunneling between two quantum wells or two layers to hybridize
Externí odkaz:
http://arxiv.org/abs/2411.01905
In pursuit of enhancing the comprehensive efficiency of production systems, our study focused on the joint optimization problem of scheduling and machine maintenance in scenarios where product rework occurs. The primary challenge lies in the interdep
Externí odkaz:
http://arxiv.org/abs/2411.01772
Autor:
Li, Jianxiong, Li, Boyang, Guo, Zhuoqiang, Li, Mingzhen, Li, Enji, Liu, Lijun, Yuan, Guojun, Wang, Zhan, Tan, Guangming, Jia, Weile
Physical phenomena such as chemical reactions, bond breaking, and phase transition require molecular dynamics (MD) simulation with ab initio accuracy ranging from milliseconds to microseconds. However, previous state-of-the-art neural network based M
Externí odkaz:
http://arxiv.org/abs/2410.22867
Autor:
Zhao, Zhihao, Faghihroohi, Shahrooz, Zhao, Yinzheng, Yang, Junjie, Zhong, Shipeng, Huang, Kai, Navab, Nassir, Li, Boyang, Nasseri, M. Ali
Background and Objective: In the realm of ophthalmic imaging, accurate vascular segmentation is paramount for diagnosing and managing various eye diseases. Contemporary deep learning-based vascular segmentation models rival human accuracy but still f
Externí odkaz:
http://arxiv.org/abs/2410.21160
Autor:
Xue, Boyang, Wang, Hongru, Wang, Rui, Wang, Sheng, Wang, Zezhong, Du, Yiming, Liang, Bin, Wong, Kam-Fai
The tendency of Large Language Models (LLMs) to generate hallucinations raises concerns regarding their reliability. Therefore, confidence estimations indicating the extent of trustworthiness of the generations become essential. However, current LLM
Externí odkaz:
http://arxiv.org/abs/2410.12478
Autor:
Wang, Hongru, Wang, Rui, Xue, Boyang, Xia, Heming, Cao, Jingtao, Liu, Zeming, Pan, Jeff Z., Wong, Kam-Fai
Large Language Models (LLMs) can interact with the real world by connecting with versatile external APIs, resulting in better problem-solving and task automation capabilities. Previous research primarily focuses on APIs with limited arguments from a
Externí odkaz:
http://arxiv.org/abs/2410.19743
Autor:
Deng, Jingyang, Shen, Zhengyang, Wang, Boyang, Su, Lixin, Cheng, Suqi, Nie, Ying, Wang, Junfeng, Yin, Dawei, Ma, Jinwen
The development of Long-Context Large Language Models (LLMs) has markedly advanced natural language processing by facilitating the process of textual data across long documents and multiple corpora. However, Long-Context LLMs still face two critical
Externí odkaz:
http://arxiv.org/abs/2410.06886