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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Tian, Pingfang Liu, Deting Department of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Institute of Scientific and Technical Information of China The Key Laboratory of the Rich Media Knowledge Organisation and Service of Digital Publishing Content Beijing100038 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan430065 China

ISBN: (纸本)9798350376548

Topic shift detection aims to identify whether there is a change in the current topic of conversation or if a change is needed. The study found previous work did not evaluate the performance of large language models like ChatGPT on the task of topic shift. Therefore, this paper's main task and innovation lie in analyzing ChatGPT's performance on topic shift detection. To provide a more comprehensive evaluation, we conducted topic shift detection tasks on ChatGPT from three aspects: single utterances, adjacent utterances, and contextual levels. Additionally, to gauge the performance of large language models, we conducted experiments on multiple small-scale models and compared the results of the two models. Experimental results on the publicly available English TIAGE dataset showed that small-scale models exhibited lower recall in all three aspects, while ChatGPT performed better in the recall. This suggests that compared to small-scale models, large models are more capable of accurately detecting topic shifts. However, large models also exhibited lower precision, indicating that while ChatGPT can recognize content differences in utterances, its judgment on whether these different contents belong to the same topic is poor. © 2024 IEEE.

关键词： adjacent utterances level ChatGPT contextual level single utterances level topic shift detection

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Multimodal Identity Recognition of Spiking Neural Network Based on Brain-Inspired Reward Propagation 22

Multimodal Identity Recognition of Spiking Neural Network Ba...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Liu, Yang Zhang, Hongxia Li, Yahui Wang, Quanqiang Liu, Cheng Henan University Henan Key Laboratory of Big Data Analysis and Processing Henan Kaifeng475004 China Henan University School of Computer and Information Engineering Henan Kaifeng475004 China Huaihe Hospital of Henan University Department of Clinical Laboratory Henan Kaifeng475004 China

ISBN: (纸本)9798331509712

Deep learning has strongly promoted the research progress of unimodal feature learning such as face recognition and speech recognition, but it still needs to be strengthened in multimodal data representation learning, especially the problem of high power consumption, which is not conducive to the real-time application of mobile devices under limited resources. In order to realize multimodal identity recognition for low-energy edge smart devices, this paper proposes a multimodal identity recognition method of spiking neural network based on brain-like mechanism (SNN-MIR-BiM). Simulating the attention mechanism of the cognitive system to specific information improves the response of multimodal features, mimics the regulation mechanism of the neurotransmitter dopamine in the nervous system, and releases reward signals from the recognition results, which affects the neuronal state and regulates the synaptic weights through global propagation, and then optimizes the network structure. Experimental results on large-scale audio and video datasets show that the proposed method can reach 98.94% recognition accuracy, and the energy consumption of the model is about 1/10 of that of CNN under the same architecture, which verifies the effectiveness of the attention mechanism and reward propagation in network design. This research is of great practical significance in the industry applications of unmanned autonomous systems such as human-computer interaction of intelligent machines and intelligent security. © 2024 IEEE.

关键词： Face recognition

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KAN v.s. MLP for Offline Reinforcement Learning

KAN v.s. MLP for Offline Reinforcement Learning

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Guo, Haihong Li, Fengxin Li, Jiao Liu, Hongyan School of Information Renmin University of China China Institute of Medical Information Medical Library Chinese Academy of Medical Sciences Peking Union Medical College China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education China School of Economics and Management Tsinghua University China

ISBN: (纸本)9798350368741

Kolmogorov-Arnold Networks (KAN) is an emerging neural network architecture in machine learning. It has greatly interested the research community about whether KAN can be a promising alternative to the commonly used Multi-Layer Perceptions (MLP). Experiments in various fields demonstrated that KAN-based machine learning can achieve comparable if not better performance than MLP-based methods, but with much smaller parameter scales and are more explainable. In this paper, we explore the incorporation of KAN into the actor and critic networks for offline reinforcement learning (RL). We evaluated the performance, parameter scales, and training efficiency of various KAN and MLP-based conservative Q-learning (CQL) on the classical D4RL benchmark for offline RL. Our study demonstrates that KAN can achieve performance close to the commonly used MLP with significantly fewer parameters. This allows us to choose the base networks according to the offline RL task requirements. © 2025 IEEE.

关键词： KAN Kolmogorov-Arnold networks MLP multilayer perceptrons offline reinforcement learning

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Tensor Graph Convolutional Network for Dynamic Graph Representation Learning 7

Tensor Graph Convolutional Network for Dynamic Graph Represe...

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7th International Symposium on Autonomous Systems, ISAS 2024

作者： Wang, Ling Yuan, Ye The School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China The Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Engineering Research Center of Big Data Application For Smart Cities Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing400714 China College of Computer and Information Science Southwest University Chongqing400715 China

ISBN: (纸本)9798350363173

Dynamic graphs (DG) represent evolving interactions between entities in various real-world scenarios. Many existing DG representation learning models employ a combination of graph convolutional networks and sequence neural networks to capture spatial-temporal dependencies. However, this hybrid approach often fails to effectively capture the spatial-temporal continuity inherent in DGs. In this paper, we propose a novel approach called the Tensor Graph Convolutional Network (TGCN) to learn DG representations within a unified convolution framework based on tensor products. Our approach is founded on two key principles: (a) representing DG information in tensor form, and (b) leveraging tensor product operations to design a graph convolutional network that simultaneously models spatial and temporal features. Experimental results on three real-world DG datasets demonstrate that our proposed model achieves state-of-the-art performance. © 2024 IEEE.

关键词： Tensors

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CLOE: Novelty Detection via Contrastive Learning with Outlier Exposure 1

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16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Liu, Tianyang Liang, Quan Yang, Hua Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China School of Mechanical Science and Engineering State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Novelty detection (ND) methods seek to identify anomalies within a specific dataset. Although self-supervised representation learning is commonly used in such applications, inadequate training data may reduce the effectiveness of these methods. It is thus reasonable to use external data to improve these performances. Here, we propose a simple and effective network, CLOE, for image-based novelty detection. Our method includes a pretrained ViT model as a feature extractor and employs the contrastive learning technique to train the dataset with external data. We compare the performance of two types of extra training settings: (1) The augmented data of the original dataset. (2) The fake images obtained from generative models. The demonstrated approach achieves a new state-of-the-art performance in novelty detection, as evidenced by achieving an ROC-AUC of 99.72% on the CIFAR-10 dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Statistics

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Stability Analysis of Mixed Traffic Flow with Connected and Autonomous Vehicles Based on Simplified DSM Model 23

Stability Analysis of Mixed Traffic Flow with Connected and ...

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23rd COTA International Conference of Transportation Professionals: Emerging data-Driven Sustainable Technological Innovation in Transportation, CICTP 2023

作者： Long, Wenmin Lu, Guangquan Liu, Miaomiao Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang Univ. Beijing China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Beihang Univ. Beijing China

ISBN: (数字)9780784485040

ISBN: (纸本)9780784485040

The applications of mobile communication and automatic driving-related technologies in transportation have made a revolution for us in traffic information perception, vehicle cooperative control, and traffic management. Besides, the emergence and development of connected vehicles (CV) and connected and autonomous vehicles (CAV) have gradually changed the traditional traffic flow into a mixed one. In order to investigate their influences and characteristics of mixed traffic flows, this paper constructs an analysis model to derive the linear stability condition of the mixed traffic flow with CV and CAV based on the simplified desired safety margin (SDSM) model. Several numerical experiments are conducted to analyze the string stability of homogeneous and heterogeneous traffic flow, respectively. The results reveal that the presence of CAV could contribute to improving the string stability as well as reducing rear-end crashes. The higher the penetration rate of CAV, the more stable the string. And the time delay in drivers and communications is not conducive to the string stability. Besides, it is also found that controllable vehicles show great potential in preventing shockwave formation and propagation, suggesting a new way in traffic flow management. © ASCE.

关键词： Cooperative communication

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Gradient-Based Differential kWTA Network With Application to Competitive Coordination of Multiple Robots

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1452-1463页

作者： Mei Liu Xiaoyan Zhang Mingsheng Shang Long Jin School of Information Science and Engineering Lanzhou UniversityLanzhou 730000 State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining 810016China Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China Shenzhen Research Institute Lanzhou UniversityShenzhen 518063China

Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)*** obtaining the network,theorems and related proofs are provided to guarantee the exponential convergence and noise resistance of the proposed GD-kWTA ***,numerical simulations are conducted to substantiate the preferable performance of the proposed network as compared with the traditional ***,the GD-k WTA network,backed with a consensus filter,is utilized as a robust control scheme for modeling the competition behavior in the multi-robot coordination,thereby further demonstrating its effectiveness and feasibility.

关键词： Consensus filter k-winners-take-all(kWTA) multirobot coordination noise resistance

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Federated Incremental Named Entity Recognition 31

Federated Incremental Named Entity Recognition

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31st International Conference on Computational Linguistics, COLING 2025

作者： Liu, Zesheng Zhu, Qiannan Li, Cuiping Chen, Hong School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Engineering Research Center of Database and Business Intelligence MOE China School of Artificial Intelligence Beijing Normal University Beijing China Engineering Research Center of Intelligent Technology and Educational Application MOE China

ISBN: (纸本)9798891761964

Federated learning-based Named Entity Recognition (FNER) has attracted widespread attention through decentralized training on local clients. However, most FNER models assume that entity types are pre-fixed, so in practical applications, local clients constantly receive new entity types without enough storage to access old entity types, resulting in severe forgetting on previously learned knowledge. In addition, new clients collecting only new entity types may join the global training of FNER irregularly, further exacerbating catastrophic forgetting. To overcome the above challenges, we propose a Forgetting-Subdued Learning (FSL) model which solves the forgetting problem on old entity types from both intra-client and inter-client two aspects. Specifically, for intra-client aspect, we propose a prototype-guided adaptive pseudo labeling and a prototypical relation distillation loss to surmount catastrophic forgetting of old entity types with semantic shift. Furthermore, for inter-client aspect, we propose a task transfer detector. It can identify the arrival of new entity types that are protected by privacy and store the latest old global model for relation distillation. Qualitative experiments have shown that our model has made significant improvements compared to several baseline methods. © 2025 Association for Computational Linguistics.

关键词： Federated learning

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The Impact of Medical Resources and Oral Antiviral Drugs on SARS-CoV-2 Mortality—Hong Kong SAR,China,2022

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China CDC weekly 2024年第21期6卷 469-477,I0001-I0005页

作者： Zhiqi Zeng Jingyi Liang Zhijie Lin Wenda Guan Wei He Qianying Li Lixi Liang Weiqi Pan Zige Liu Guibin Lu Xiaoyan Deng Eric HY Lau Chitin Hon Zifeng Yang Guangzhou key laboratory for clinical rapid diagnosis and early warning of infectious diseases KingMed School of Laboratory MedicineGuangzhou Medical UniversityGuangzhou CityGuangdong ProvinceChina Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao SARChina Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovative EngineeringMacao University of Science and TechnologyMacao SARChina State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory Healththe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou CityGuangdong ProvinceChina School of Public Health The University of Hong KongHong Kong SARChina Laboratory of Data Discovery for Health Hong Kong SARChina Guangzhou Laboratory Guangzhou CityGuangdong ProvinceChina

Introduction:The Omicron variant of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)demonstrates increased transmissibility compared to earlier strains,contributing to a significant number of fatalities in Hong Kong Special Administrative Region(HKSAR),*** medical resources and medications are essential in mitigating these *** study evaluates the effects of supplementary resources from the Chinese mainland during the fifth wave of the pandemic in ***:Vector autoregression(VAR)was employed to analyze data from the Oxford coronavirus disease 2019(COVID-19)Government Response Tracker to assess the effectiveness of control measures during five waves of the pandemic in ***,a transmission dynamics model was created to investigate the influence of supplementary medical resources from the Chinese mainland and oral medications on ***:In the initial four waves,workplace closures,restrictions on public events,international travel bans,and shielding the elderly significantly influenced pandemic ***,during the fifth wave,these measures showed no notable *** comparing a situation without extra medical resources or COVID-19 oral medication,there was a 17.7%decrease in COVID-19 fatalities with mainland medical resources and an additional 10.2%reduction with oral ***,they contributed to a 26.6%decline in ***:With the rapid spread of the virus,regional reallocation of medical resources may reduce mortality even when the local healthcare system is overstretched.

关键词： mainland Impact travel

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Eu3+ co-doped broadband yellow-emitting BaZnSiO4: Bi3+ phosphors for multifunctional applications

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Ceramics International 2025年

作者： Li, Bin Cao, Bin Yang, Chong Ma, Rongbo Deng, Chaoyong Huang, Weichao Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guizhou Guiyang550025 China

Bi3+-activated phosphors have received increasing attention due to their abundant emission properties. In this paper, a series of BaZnSiO4: Bi3+ phosphors have been synthesized and structurally characterized, and the correlations between their structure and luminescence were also studied systematically. Under 306 nm excitation, the phosphors show broadband yellow emission centered at 559 nm with a full width at half-maximum (FWHM) of 123 nm, resulting from the 3P1/1P1 → 1S0 transition of Bi3+. Thermal stability spectroscopy of BaZnSiO4: Bi3+ phosphor was found to have the potential for application in optical temperature sensing with a Sr value of 2.2 % K−1. BaZnSiO4: Bi3+ phosphors were also used to explore flexible display and lighting. In addition, the color change function is realized by Eu3+ co-doping, which shows good potential application value in the field of anti-counterfeiting. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Phosphors

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