Frontiers of Computer Science最新文献_第2页

Generalized splitting-ring number theoretic transform 广义分环数论变换

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-04-08 DOI: 10.1007/s11704-024-3288-9

Zhichuang Liang, Yunlei Zhao, Zhenfeng Zhang

引用次数: 0

Massively parallel algorithms for fully dynamic all-pairs shortest paths 全动态全对最短路径的大规模并行算法

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-04-08 DOI: 10.1007/s11704-024-3452-2

Chilei Wang, Qiang-Sheng Hua, Hai Jin, Chaodong Zheng

引用次数: 0

A survey on large language model based autonomous agents 基于大型语言模型的自主代理调查

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-03-22 DOI: 10.1007/s11704-024-40231-1

Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, Wayne Xin Zhao, Zhewei Wei, Jirong Wen

{"title":"A survey on large language model based autonomous agents","authors":"Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, Wayne Xin Zhao, Zhewei Wei, Jirong Wen","doi":"10.1007/s11704-024-40231-1","DOIUrl":"https://doi.org/10.1007/s11704-024-40231-1","url":null,"abstract":"Autonomous agents have long been a research focus in academic and industry communities. Previous research often focuses on training agents with limited knowledge within isolated environments, which diverges significantly from human learning processes, and makes the agents hard to achieve human-like decisions. Recently, through the acquisition of vast amounts of Web knowledge, large language models (LLMs) have shown potential in human-level intelligence, leading to a surge in research on LLM-based autonomous agents. In this paper, we present a comprehensive survey of these studies, delivering a systematic review of LLM-based autonomous agents from a holistic perspective. We first discuss the construction of LLM-based autonomous agents, proposing a unified framework that encompasses much of previous work. Then, we present a overview of the diverse applications of LLM-based autonomous agents in social science, natural science, and engineering. Finally, we delve into the evaluation strategies commonly used for LLM-based autonomous agents. Based on the previous studies, we also present several challenges and future directions in this field.","PeriodicalId":12640,"journal":{"name":"Frontiers of Computer Science","volume":"304 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140199133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SCREEN: predicting single-cell gene expression perturbation responses via optimal transport SCREEN：通过优化传输预测单细胞基因表达扰动反应

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-03-22 DOI: 10.1007/s11704-024-31014-9

Haixin Wang, Yunhan Wang, Qun Jiang, Yan Zhang, Shengquan Chen

引用次数: 0

A biased edge enhancement method for truss-based community search 基于桁架的群体搜索的偏置边缘增强法

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-03-15 DOI: 10.1007/s11704-024-2604-8

Yuqi Li, Tao Meng, Zhixiong He, Haiyan Liu, Keqin Li

引用次数: 0

XGCN: a library for large-scale graph neural network recommendations XGCN：大规模图神经网络推荐库

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-03-15 DOI: 10.1007/s11704-024-3803-z

Xiran Song, Hong Huang, Jianxun Lian, Hai Jin

引用次数: 0

Uncertain knowledge graph embedding: an effective method combining multi-relation and multi-path 不确定知识图谱嵌入：一种结合多关系和多路径的有效方法

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-01-23 DOI: 10.1007/s11704-023-2427-z

Qi Liu, Qinghua Zhang, Fan Zhao, Guoyin Wang

{"title":"Uncertain knowledge graph embedding: an effective method combining multi-relation and multi-path","authors":"Qi Liu, Qinghua Zhang, Fan Zhao, Guoyin Wang","doi":"10.1007/s11704-023-2427-z","DOIUrl":"https://doi.org/10.1007/s11704-023-2427-z","url":null,"abstract":"Uncertain Knowledge Graphs (UKGs) are used to characterize the inherent uncertainty of knowledge and have a richer semantic structure than deterministic knowledge graphs. The research on the embedding of UKG has only recently begun, Uncertain Knowledge Graph Embedding (UKGE) model has a certain effect on solving this problem. However, there are still unresolved issues. On the one hand, when reasoning the confidence of unseen relation facts, the introduced probabilistic soft logic cannot be used to combine multi-path and multi-step global information, leading to information loss. On the other hand, the existing UKG embedding model can only model symmetric relation facts, but the embedding problem of asymmetric relation facts has not be addressed. To address the above issues, a Multiplex Uncertain Knowledge Graph Embedding (MUKGE) model is proposed in this paper. First, to combine multiple information and achieve more accurate results in confidence reasoning, the Uncertain ResourceRank (URR) reasoning algorithm is introduced. Second, the asymmetry in the UKG is defined. To embed asymmetric relation facts of UKG, a multi-relation embedding model is proposed. Finally, experiments are carried out on different datasets via 4 tasks to verify the effectiveness of MUKGE. The results of experiments demonstrate that MUKGE can obtain better overall performance than the baselines, and it helps advance the research on UKG embedding.","PeriodicalId":12640,"journal":{"name":"Frontiers of Computer Science","volume":"31 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139559959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of human microRNA-disease association via low-rank approximation-based link propagation and multiple kernel learning 通过基于低秩近似的链接传播和多核学习识别人类 microRNA 与疾病的关联性

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-01-22 DOI: 10.1007/s11704-023-2490-5

Yizheng Wang, Xin Zhang, Ying Ju, Qing Liu, Quan Zou, Yazhou Zhang, Yijie Ding, Ying Zhang

引用次数: 0

Unsupervised social network embedding via adaptive specific mappings 通过自适应特定映射实现无监督社交网络嵌入

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-01-22 DOI: 10.1007/s11704-023-2180-3

Youming Ge, Cong Huang, Yubao Liu, Sen Zhang, Weiyang Kong

{"title":"Unsupervised social network embedding via adaptive specific mappings","authors":"Youming Ge, Cong Huang, Yubao Liu, Sen Zhang, Weiyang Kong","doi":"10.1007/s11704-023-2180-3","DOIUrl":"https://doi.org/10.1007/s11704-023-2180-3","url":null,"abstract":"In this paper, we address the problem of unsuperised social network embedding, which aims to embed network nodes, including node attributes, into a latent low dimensional space. In recent methods, the fusion mechanism of node attributes and network structure has been proposed for the problem and achieved impressive prediction performance. However, the non-linear property of node attributes and network structure is not efficiently fused in existing methods, which is potentially helpful in learning a better network embedding. To this end, in this paper, we propose a novel model called ASM (Adaptive Specific Mapping) based on encoder-decoder framework. In encoder, we use the kernel mapping to capture the non-linear property of both node attributes and network structure. In particular, we adopt two feature mapping functions, namely an untrainable function for node attributes and a trainable function for network structure. By the mapping functions, we obtain the low dimensional feature vectors for node attributes and network structure, respectively. Then, we design an attention layer to combine the learning of both feature vectors and adaptively learn the node embedding. In encoder, we adopt the component of reconstruction for the training process of learning node attributes and network structure. We conducted a set of experiments on seven real-world social network datasets. The experimental results verify the effectiveness and efficiency of our method in comparison with state-of-the-art baselines.","PeriodicalId":12640,"journal":{"name":"Frontiers of Computer Science","volume":"6 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139559960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CompactChain: an efficient stateless chain for UTXO-model blockchain CompactChain：适用于UTXO模式区块链的高效无状态链

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2024-01-22 DOI: 10.1007/s11704-023-2365-9

B. Swaroopa Reddy, T. Uday Kiran Reddy

{"title":"CompactChain: an efficient stateless chain for UTXO-model blockchain","authors":"B. Swaroopa Reddy, T. Uday Kiran Reddy","doi":"10.1007/s11704-023-2365-9","DOIUrl":"https://doi.org/10.1007/s11704-023-2365-9","url":null,"abstract":"In this work, we propose a stateless blockchain called CompactChain, which compacts the entire state of the UTXO (Unspent Transaction Output) based blockchain systems into two RSA accumulators. The first accumulator is called Transaction Output (TXO) commitment which represents the TXO set. The second one is called Spent Transaction Output (STXO) commitment which represents the STXO set. In this work, we discuss three algorithms: (i) To update the TXO and STXO commitments by the miner. The miner also provides the proofs for the correctness of the updated commitments; (ii) To prove the transaction’s validity by providing a membership witness in TXO commitment and non-membership witness against STXO commitment for a coin being spent by a user; (iii) To update the witness for the coin that is not yet spent; The experimental results evaluate the performance of the CompactChain in terms of time taken by a miner to update the commitments and time taken by a validator to verify the commitments and validate the transactions. We compare the performance of CompactChain with the existing state-of-the-art works on stateless blockchains. CompactChain shows a reduction in commitments update complexity and transaction witness size which inturn reduces the mempool size and propagation latency without compromising the system throughput (Transactions per second (TPS)).","PeriodicalId":12640,"journal":{"name":"Frontiers of Computer Science","volume":"2 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139559868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0