《Frontiers of Computer Science》

作品数：1375被引量：1928H指数：15
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《Frontiers of Computer Science》
主办单位：Higher Education Press, China ;Beihang University, China
最新期次：2025年4期更多>>
发文主题：LEARNINGGRAPHSURVEYBASED_ONED更多>>
发文领域：自动化与计算机技术理学电子电信建筑科学更多>>
发文基金：国家自然科学基金国家重点基础研究发展计划中国博士后科学基金国家高技术研究发展计划更多>>
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ACbot:an IIoT platform for industrial robots
《Frontiers of Computer Science》2025年第4期13-27,共15页Rui WANG Xudong MOU Tianyu WO Mingyang ZHANG Yuxin LIU Tiejun WANG Pin LIU Jihong YAN Xudong LIU 
supported by the Zhejiang Province Key R&D Program of China(2023C01070).
As the application of Industrial Robots(IRs)scales and related participants increase,the demands for intelligent Operation and Maintenance(O&M)and multi-tenant collaboration rise.Traditional methods could no longer co...
关键词：IIoT platform industrial robots cloud-edge collaboration intelligent applications 
A multi-projection recurrent model for hypernym detection and discovery
《Frontiers of Computer Science》2025年第4期29-42,共14页Xuefeng ZHANG Junfan CHEN Zheyan LUO Yuhang BAI Chunming HU Richong ZHANG 
supported by the National Science and Technology Major Project of China(2022ZD0120202);the Natural Natural Science Foundation of China(Grant No.U23B2056).
Hypernym detection and discovery are fundamental tasks in natural language processing.The former task aims to identify all possible hypernyms of a given hyponym term,whereas the latter attempts to determine whether th...
关键词：natural language processing hypernym detection recurrent model 
Clustered Reinforcement Learning
《Frontiers of Computer Science》2025年第4期43-57,共15页Xiao MA Shen-Yi ZHAO Zhao-Heng YIN Wu-Jun LI 
supported by the National Natural Science Foundation of China(Gtant No.62192783);Fundamental Research Funds for the Central Universities(No.020214380108).
Exploration strategy design is a challenging problem in reinforcement learning(RL),especially when the environment contains a large state space or sparse rewards.During exploration,the agent tries to discover unexplor...
关键词：deep reinforcement learning EXPLORATION count-based method CLUSTERING K-MEANS 
Open and real-world human-AI coordination by heterogeneous training with communication
《Frontiers of Computer Science》2025年第4期59-76,共18页Cong GUAN Ke XUE Chunpeng FAN Feng CHEN Lichao ZHANG Lei YUAN Chao QIAN Yang YU 
supported by the National Key Research and Development Program of China(2020AAA0107200);the National Natural Science Foundation of China(Grant Nos.61921006,61876119,62276126);the Natural Science Foundation of Jiangsu(BK20221442).
Human-AI coordination aims to develop AI agents capable of effectively coordinating with human partners,making it a crucial aspect of cooperative multi-agent reinforcement learning(MARL).Achieving satisfying performan...
关键词：human-AI coordination multi-agent reinforcement learning COMMUNICATION open-environment coordination real-world coordination 
Offline model-based reinforcement learning with causal structured world models
《Frontiers of Computer Science》2025年第4期77-90,共14页Zhengmao ZHU Honglong TIAN Xionghui CHEN Kun ZHANG Yang YU 
Model-based methods have recently been shown promising for offline reinforcement learning(RL),which aims at learning good policies from historical data without interacting with the environment.Previous model-based off...
关键词：reinforcement learning offline reinforcement learning model-based reinforcement learning causal discovery 
On the exact quantum query complexity of MOD and EXACT functions
《Frontiers of Computer Science》2025年第4期91-98,共8页Penghui YAO Zekun YE 
supported by the National Natural Science Foundation of China(Grant Nos.62332009,12347104,and 61972191);the Innovation Program for Quantum Science and Technology(2021ZD0302901).
In this paper,we consider the exact quantum query complexity of two fundamental symmetric functions.1)MOD_(m)^(n),which calculates the Hamming weight of an-bit string modulo;2)EXACT_(k,l)^(n),which determines if the H...
关键词：quantum computing query complexity symmetric functions exact algorithms evasiveness 
Computational approaches for circRNA-disease association prediction:a review
《Frontiers of Computer Science》2025年第4期99-113,共15页Mengting NIU Yaojia CHEN Chunyu WANG Quan ZOU Lei XU 
supported by the National Natural Science Foundation of China(Grant Nos.62231013,62201129,62303328,62302341,62271329,62372332);the National Key R&D Program of China(2022ZD0117700);the National funded postdoctoral researcher program of China(GZC20230382);the Shenzhen Polytechnic University Research Fund(6024310027K,6022310036K,6023310037K);the Key Field of Department of Education of Guangdong Province(2022ZDZX2082);the Special Science Foundation of Quzhou(2023D036).
Circular RNA(circRNA)is a covalently closed RNA molecule formed by back splicing.The role of circRNAs in posttranscriptional gene regulation provides new insights into several types of cancer and neurological diseases...
关键词：circular RNA disease association prediction machine learning data mining deep learning 
Large language models make sample-efficient recommender systems
《Frontiers of Computer Science》2025年第4期115-117,共3页Jianghao LIN Xinyi DAI Rong SHAN Bo CHEN Ruiming TANG Yong YU Weinan ZHANG 
supported by the National Natural Science Foundation of China(Grant No.62177033).
1 Introduction Large language models(LLMs)have achieved remarkable progress in the field of natural language processing(NLP),showing impressive abilities to generate human-like texts for a broad range of tasks[1].Cons...
关键词：recommendation tasksand recommender systemsthey recommender systems large language models large language models llms recommender sy promoting sample efficiency natural language processing nlp showing 
Agents with foundation models:advance and vision
《Frontiers of Computer Science》2025年第4期119-120,共2页Chenghua GONG Xiang LI 
1 Introduction With rapid development in computing power and breakthroughs in deep learning,the concept of“foundation models”has been introduced into the AI community.Generally,foundation models are large models tra...
关键词：computing power foundation models adapted different domains animate scenarios deep learningthe massive data generate texts imagesor deep learning 
LLaVA-Endo:a large language-and-vision assistant for gastrointestinal endoscopy
《Frontiers of Computer Science》2025年第4期121-123,共3页Jieru YAO Xueran LI Qiang XIE Longfei HAN Yiwen JIA Nian LIU Dingwen ZHANG Junwei HAN 
supported in part by the National Natural Science Foundation of China(Grant Nos.62272468,62003256,62027813,U1801265,62293543,62322605,62036005,62202015,and U21B2048);the Key-Area Research and Development Program of Shaanxi Province(2023-ZDLSF-41);the Anhui Medical University(2022xkj105,2023cy021);the Anhui Provincial Key R&D Program(2023s07020001);the University Synergy Innovation Program of Anhui Province(GXXT-2022-052).
1 Introduction Endoscopy plays a crucial role in the diagnoses and treatment of gastrointestinal(GI)diseases[1],as it helps to identify abnormalities,classify lesion,and determine treatment methods.During GI endoscopi...
关键词：STRESS giendoscopy FATIGUE identify abnormalitiesclassify lesionidentification ARTIFICIALINTELLIGENCE 
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