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COVID-19 spreading patterns in family clusters reveal gender roles in China

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arXiv 2023年

作者： Liao, Jingyi Liu, Xiao Fan Xu, Xiao-Ke Zhou, Tao Big Data Research Center University of Electronic Science and Technology of China Chengdu China Web Mining Laboratory Department of Media and Communication City University of Hong Kong Hong Kong College of Information and Communication Engineering Dalian Minzu University Dalian China

Unfolding different gender roles is preceding the efforts to reduce gender inequality. This paper analyzes COVID-19 family clusters outside Hubei Province in mainland China during the 2020 outbreak, revealing significant differences in spreading patterns across gender and family roles. Results show that men are more likely to be the imported cases of a family cluster, and women are more likely to be infected within the family. This finding provides new supportive evidence of the "men as breadwinner and women as homemaker" (MBWH) gender roles in China. Further analyses reveal that the MBWH pattern is stronger in eastern than in western China, stronger for younger than for elder people. This paper offers not only valuable references for formulating gender-differentiated epidemic prevention policies but also an exemplification for studying group differences in similar scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： COVID-19

PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference

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arXiv 2024年

作者： Yang, Dongjie Han, Xiaodong Gao, Yan Hu, Yao Zhang, Shilin Zhao, Hai Shanghai Jiao Tong University China Xiaohongshu Inc. China South China University of Technology China The Department of Computer Science and Engineering Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

Large Language Models (LLMs) have shown remarkable comprehension abilities but face challenges in GPU memory usage during inference, hindering their scalability for real-time applications like chatbots. To accelerate inference, we store computed keys and values (KV cache) in the GPU memory. Existing methods study the KV cache compression to reduce memory by pruning the pre-computed KV cache. However, they neglect the inter-layer dependency between layers and huge memory consumption in pre-computation. To explore these deficiencies, we find that the number of crucial keys and values that influence future generations decreases layer by layer and we can extract them by the consistency in attention weights. Based on the findings, we propose PyramidInfer, a method that compresses the KV cache by layer-wise retaining crucial context. PyramidInfer saves significant memory by computing fewer keys and values without sacrificing performance. Experimental results show PyramidInfer improves 2.2x throughput compared to Accelerate with over 54% GPU memory reduction in KV cache. Our code is available in https://***/mutonix/ pyramidinfer. © 2024, CC BY.

关键词： Cache memory

On the Robustness of Editing Large Language Models

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arXiv 2024年

作者： Ma, Xinbei Ju, Tianjie Qiu, Jiyang Zhang, Zhuosheng Zhao, Hai Liu, Lifeng Wang, Yulong School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China Baichuan Intelligent Technology China

Large language models (LLMs) have played a pivotal role in building communicative AI, yet they encounter the challenge of efficient updates. Model editing enables the manipulation of specific knowledge memories and the behavior of language generation without retraining. However, the robustness of model editing remains an open question. This work seeks to understand the strengths and limitations of editing methods, facilitating practical applications of communicative AI. We focus on three key research questions. RQ1: Can edited LLMs behave consistently resembling communicative AI in realistic situations? RQ2: To what extent does the rephrasing of prompts lead LLMs to deviate from the edited knowledge memory? RQ3: Which knowledge features are correlated with the performance and robustness of editing? Our empirical studies uncover a substantial disparity between existing editing methods and the practical application of LLMs. On rephrased prompts that are flexible but common in realistic applications, the performance of editing experiences a significant decline. Further analysis shows that more popular knowledge is memorized better, easier to recall, and more challenging to edit effectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Computational linguistics

A Simple Standard for Ontological Mappings 2023: Updates on data model, collaborations and tooling 18

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A Simple Standard for Ontological Mappings 2023: Updates on ...

18th International Workshop on Ontology Matching, OM 2023

作者： Matentzoglu, Nicolas Braun, Ian Caron, Anita R. Goutte-Gattat, Damien Gyori, Benjamin M. Harris, Nomi L. Hartley, Emily Hegde, Harshad B. Hertling, Sven Hoyt, Charles Tapley Kim, HyeongSik Li, Huanyu McLaughlin, James Trojahn, Cassia Vasilevsky, Nicole Mungall, Christopher J. Semanticly Athens Greece University of Cambridge CambridgeCB2 3DY United Kingdom Harvard Medical School BostonMA02115 United States Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Critical Path Institute TucsonAZ85718 United States Data and Web Science Group University of Mannheim Germany Robert Bosch LLC United States Linköping University Linköping Sweden Universite Toulouse 2 Toulouse France Hinxton United Kingdom

The Simple Standard for Ontological Mappings (SSSOM) was first published in December 2021 (v. 0.9). After a number of revisions prompted by community feedback, we have published version 0.15.0 in July 2023. Here we report on the progress made since August 2022, in particular changes to tooling, data model and summary of ongoing standardisation efforts. © 2023 Copyright for this paper by its authors.

关键词： FAIR data mappings ontologies ontology mapping standards

GLaPE: Gold Label-agnostic Prompt Evaluation and Optimization for Large Language Model

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arXiv 2024年

作者： Zhang, Xuanchang Zhang, Zhuosheng Zhao, Hai College of Zhiyuan Shanghai Jiao Tong University China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

Despite the rapid progress of large language models (LLMs), their task performance remains sensitive to prompt design. Recent studies have explored leveraging the LLM itself as an optimizer to identify optimal prompts that maximize task accuracy. However, when evaluating prompts, such approaches heavily rely on elusive manually annotated gold labels to calculate task accuracy for each candidate prompt, which hinders its generality. To overcome the limitation, this work proposes GLaPE, a gold label-agnostic prompt evaluation method to alleviate dependence on gold labels. GLaPE is composed of two critical aspects: self-consistency evaluation of a single prompt and mutual-consistency refinement across multiple prompts. Experimental results on 8 widely-recognized reasoning tasks demonstrate that GLaPE can produce more effective prompts, achieving performance comparable to those derived from manually annotated gold labels. Analysis shows that GLaPE provides reliable evaluations aligned with accuracy, even in the absence of gold labels. Code is publicly available at https://***/thunderous77/GLaPE. Copyright © 2024, The Authors. All rights reserved.

关键词： Gold

How Deep is Love in LLMs’ Hearts? Exploring Semantic Size in Human-like Cognition

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arXiv 2025年

作者： Yao, Yao Yang, Yifei Ma, Xinbei Yang, Dongjie Zhang, Zhuosheng Li, Zuchao Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 Shanghai China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan University Wuhan430072 China

How human cognitive abilities are formed has long captivated researchers. However, a significant challenge lies in developing meaningful methods to measure these complex processes. With the advent of large language models (LLMs), which now rival human capabilities in various domains, we are presented with a unique testbed to investigate human cognition through a new lens. Among the many facets of cognition, one particularly crucial aspect is the concept of semantic size—the perceived magnitude of both abstract and concrete words or concepts. This study seeks to investigate whether LLMs exhibit similar tendencies in understanding semantic size, thereby providing insights into the underlying mechanisms of human cognition. We begin by exploring metaphorical reasoning, comparing how LLMs and humans associate abstract words with concrete objects of varying sizes. Next, we examine LLMs’ internal representations to evaluate their alignment with human cognitive processes. Our findings reveal that multi-modal training is crucial for LLMs to achieve more human-like understanding, suggesting that real-world, multi-modal experiences are similarly vital for human cognitive development. Lastly, we examine whether LLMs are influenced by attention-grabbing headlines with larger semantic sizes in a real-world web shopping scenario. The results show that multi-modal LLMs are more emotionally engaged in decision-making, but this also introduces potential biases, such as the risk of manipulation through clickbait headlines. Ultimately, this study offers a novel perspective on how LLMs interpret and internalize language, from the smallest concrete objects to the most profound abstract concepts like ‘love’. The insights gained not only improve our understanding of LLMs but also provide new avenues for exploring the cognitive abilities that define human intelligence. Our code and dataset is publicly available at https://***/Zoeyyao27/LLM-Semantic-Size-Understanding. © 2025, CC BY.

关键词： Semantics

Heterogeneous influence of individuals’ behavior on mask efficacy in gathering environments

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Frontiers of Engineering Management 2022年第4期9卷 550-562页

作者： Haochen SUN Xiaofan LIU Zhanwei DU Ye WU Haifeng ZHANG Xiaoke XU College of Information and Communication Engineering Dalian Minzu UniversityDalian 116600China Web Mining Laboratory Department of Media and CommunicationCity University of Hong KongHong KongChina WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong KongChina Laboratory of Data Discovery for Health Hong Kong Science and Technology ParkHong KongChina Computational Communication Research Center Beijing Normal University(Zhuhai)Zhuhai 519087China School of Journalism and Communication Beijing Normal UniversityBeijing 100875China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical ScienceAnhui UniversityHefei 230601China

Wearing masks is an easy way to operate and popular measure for preventing *** masks can slow down the spread of viruses,their efficacy in gathering environments involving heterogeneous person-to-person contacts remains ***,we aim to investigate the epidemic prevention effect of masks in different real-life gathering *** study uses four real interpersonal contact datasets to construct four empirical networks to represent four gathering *** transmission of COVID-19 is simulated using the Monte Carlo simulation *** heterogeneity of individuals can cause mask efficacy in a specific gathering environment to be different from the baseline efficacy in general ***,the heterogeneity of gathering environments causes the epidemic prevention effect of masks to *** masks can greatly reduce the probability of clustered epidemics and the infection scale in primary schools,high schools,and ***,the use of masks alone in primary schools and hospitals cannot control *** high schools with social distancing between classes and in workplaces where the interpersonal contact is relatively sparse,masks can meet the need for *** the heterogeneity of individual behavior,if individuals who are more active in terms of interpersonal contact are prioritized for mask-wearing,the epidemic prevention effect of masks can be ***,asymptomatic infection has varying effects on the prevention effect of masks in different *** effect can be weakened or eliminated by increasing the usage rate of masks in high schools and ***,the effect on primary schools and hospitals cannot be *** study contributes to the accurate evaluation of mask efficacy in various gathering environments to provide scientific guidance for epidemic prevention.

关键词： COVID-19 masks behavioral heterogeneity asymptomatic infection

Practical Iterative Quantum Consensus Protocol with Sharding Construction

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IEEE Journal on Selected Areas in Communications 2025年

作者： Ying, Chenhao Du, Yuxuan Zhang, Weiting Jiang, Xikun Wang, Gang Jin, Haiming Li, Jie Luo, Yuan Tao, Dacheng Shanghai Jiao Tong University Department of Computer Science Shanghai China Zhejiang University Shanghai Jiao Tong University State Key Laboratory of Blockchain and Data Security Blockchain Advanced Research Center Jiangsu Wuxi214101 China Nanyang Technological University College of Computing&Data Science Singapore Beijing Jiaotong University School of Electronic and Information Engineering Beijing China University of Copenhagen Department of Computer Science Denmark Northeastern University School of Computer Science and Engineering Shenyang China Shanghai Key Laboratory of Trusted Data Circulation and Governance Web3 China

With the development of quantum blockchain, the quantum consensus protocols have garnered increasing attention, which play a crucial role in driving the implementation of quantum blockchains. However, existing protocols, derived from the classical consensus algorithms, face practical application challenges due to current quantum technology limitations. The first challenge is the bottleneck in generating large-scale entangled quantum states. The second challenge arises from the generation of malicious quantum states. The final challenge involves privacy concerns. To address these challenges, we propose a practical iterative QUantum consensus protocol with sharding construction, namely, Q-Union. In fact, Q-Union employs an iterative consensus algorithm where participating nodes are divided into multiple smaller shards, with the consensus process occurring within the current shard, and new shards are involved only if consensus is not achieved. Leveraging Greenberger-Horne- Zeilinge states and Aharonov states, Q-Union harnesses the advantages of quantum mechanics to achieve anonymous consensus, protecting the private information of participating nodes. Additionally, by integrating state verification, Q-Union ensures the correctness of the consensus procedure in the presence of malicious nodes generating adversarial quantum states. Finally, it is proven that Q-Union can also defend against Byzantine attacks from adversarial nodes, maintaining the same security level as traditional non-sharded consensus protocols. Specifically, it consistently outputs the correct consensus when the fraction of adversaries among participating nodes is less than 1/2 with synchronous communication. Both the theoretical analysis and performance illustration demonstrate the superior performance of the proposed Q-Union compared to state-of-the-art protocols. © 1983-2012 IEEE.

关键词： Quantum entanglement

Magnetic activities and parameters of 43 flare stars in the GWAC archive

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arXiv 2022年

作者： Li, Guang-Wei Wu, Chao Zhou, Gui-Ping Yang, Chen Li, Hua-Li Chen, Jie Xin, Li-Ping Wang, Jing Haerken, Hasitieer Ma, Chao-Hong Cai, Hong-Bo Han, Xu-Hui Huang, Lei Lu, Xiao-Meng Bai, Jian-Ying Zhang, Xu-Kang Hao, Xin-Li Wang, Xiang-Yu Dai, Zi-Gao Liang, En-Wei Meng, Xiao-Feng Wei, Jian-Yan Key laboratory of Space Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Key laboratory of Solar Activity National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Lab of Web and Mobile Data Management Renmin University of China Beijing100872 China Guangxi Key Laboratory for Relativistic Astrophysics School of Physical Science and Technology Guangxi University Nanning530004 China School of Artificial Intelligence of Beijing Normal University No.19 Xinjiekouwai St Haidian District Beijing100875 China School of Astronomy and Space Science Nanjing University Nanjing210093 China Ministry of Education Nanjing210093 China

In the archive of the Ground Wide Angle Camera (GWAC), we found 43 white light flares from 43 stars, among which, three are sympathetic or homologous flares, and one of them also has a quasi-periodic pulsation with a period of 13.0 ± 1.5 minutes. Among these 43 flare stars, there are 19 new active stars and 41 stars that have available TESS and/or K2 light curves, from which we found 931 stellar flares. We also obtained rotational or orbital periods of 34 GWAC flare stars, of which 33 are less than 5.4 days, and ephemerides of three eclipsing binaries from these light curves. Combining with low resolution spectra from LAMOST and the Xinglong 2.16m telescope, we found that LHα/Lbol are in the saturation region in the rotation-activity diagram. From the LAMOST medium-resolution spectrum, we two components are both active stars. Thirteen stars have flare frequency distributions (FFDs) from TESS and/or K2 light curves. These FFDs show that the flares detected by GWAC can occur at a frequency of 0.5 to 9.5 yr−1. The impact of flares on habitable planets was also studied based on these FFDs, and flares from some GWAC flare stars may produce enough energetic flares to destroy ozone layers, but none can trigger prebiotic chemistry on their habitable planets. © 2022, CC0.

关键词： Planets