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31st International Conference on Computational Linguistics, COLING 2025

作者： Cao, Jincheng Li, Bobo Liu, Jiang Ji, Donghong Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University Wuhan China

ISBN: (纸本)9798891761964

Entity and relation extraction is a conventional task in the field of information extraction. Existing work primarily focuses on detecting specific relations between entities, often constrained to particular fields and lacking general applicability. In response, we propose a novel task: nominal compound relation extraction (NCRE), which concentrates on abstract and broadly applicable relation extraction between noun phrases. This task diverges significantly from traditional entity and relation extraction in two key respects. Firstly, our task involves general nominal compounds rather than named entities, which are longer and encompass a broader scope, presenting significant challenges for extraction. Secondly, relation extraction in NCRE demands an in-depth understanding of context to detect abstract relations. We manually annotate a high-quality Chinese dataset for the NCRE task and develop a model incorporating the rotary position-enhanced word pair (RoWP) detection schema. Experimental results demonstrate the efficiency of our RoWP model over previous baselines, while the suboptimal F1 scores indicate that NCRE remains a challenging task. Our code and data are available at https://***/yeecjc/NCRE. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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An Improved YOLOv5s-Based Smoke Detection System for Outdoor Parking Lots

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Computers, Materials & Continua 2024年第8期80卷 3333-3349页

作者： Ruobing Zuo Xiaohan Huang Xuguo Jiao Zhenyong Zhang State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China School of Information and Control Engineering Qingdao University of TechnologyQingdao266520China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou310027China Key Laboratory of Computing Power Network and Information Security Ministry of EducationQilu University of Technology(Shandong Academy of Sciences)Jinan250353China Text Computing&Cognitive Intelligence Engineering Research Center of National Education Ministry Guizhou UniversityGuiyang550025China

In the rapidly evolving urban landscape,outdoor parking lots have become an indispensable part of the city’s transportation *** growth of parking lots has raised the likelihood of spontaneous vehicle combus-tion,a significant safety hazard,making smoke detection an essential preventative ***,the complex environment of outdoor parking lots presents additional challenges for smoke detection,which necessitates the development of more advanced and reliable smoke detection *** paper addresses this concern and presents a novel smoke detection technique designed for the demanding environment of outdoor parking ***,we develop a novel dataset to fill the gap,as there is a lack of publicly available *** dataset encompasses a wide range of smoke and fire scenarios,enhanced with data augmentation to ensure robustness against diverse outdoor ***,we utilize an optimized YOLOv5s model,integrated with the Squeeze-and-Excitation Network(SENet)attention mechanism,to significantly improve detection accuracy while maintaining real-time processing ***,this paper implements an outdoor smoke detection system that is capable of accurately localizing and alerting in real time,enhancing the effectiveness and reliability of emergency *** show that the system has a high accuracy in terms of detecting smoke incidents in outdoor scenarios.

关键词： YOLOv5s smoke detection deep learning SENet

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3DGCformer: 3-Dimensional Graph Convolutional transformer for multi-step origin–destination matrix forecasting

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Applied Intelligence 2025年第6期55卷 1-18页

作者： Huang, Yiou Deng, Hao Zhao, Shengjie School of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Shanghai China Engineering Research Center of Key Software Technologies for Smart City Perception and Planning Ministry of Education Shanghai China

Forecasting Human mobility is of great significance in the simulation and control of infectious diseases like COVID-19. To get a clear picture of potential future outbreaks, it is necessary to forecast multi-step Origin–Destination (OD) matrices for a relatively long period in the future. However, multi-step Origin–Destination Matrix Forecasting (ODMF) is a non-trivial problem. First, previous ODMF models only forecast the OD matrix for the next time-step, and they cannot perform well on long-term multi-step forecasts due to error accumulation. Second, many ODMF methods capture spatial and temporal dependencies with separate modules, which is insufficient to model spatio-temporal correlations in the time-varying OD matrix sequence. To address the challenges in multi-step ODMF, we propose 3-Dimensional Graph Convolutional Transformer (3DGCformer). As an enhancement of the original 3DGCN, we propose a novel Origin–Destination Feature Propagation (ODFP) rule between 3DGCN layers and integrate 2 3DGCNs with different spatio-temporal graphs and corresponding feature propagation rules to model the formation of OD flows in a more comprehensive way. For multi-step forecasts, 3DGCformer uses Transformer to capture long-term global temporal dependency, and adapt its decoder using labeled tokens to avoid error accumulation and improve time efficiency. To avoid information loss as the number of regions increases, we propose a patch embedding approach to convert data from 3DGCNs to the Transformer module. We perform extensive experiments on 4 real-world human mobility datasets, and the results show that our proposed model outperforms the state-of-the-art methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolution

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CRISPR-Mediated rDNA Integration and Fluorescence Screening for Pathway Optimization in Pichia pastoris

Chem and Bio Engineering

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Chem and Bio engineering 2024年第11期1卷 940-951页

作者： Jiang, Xiaojing Li, Mengxin Wang, Zhijiao Ye, Cuifang Gao, Jucan Ai, Xiaowei Bao, Jingfei Cheng, Jintao Lian, Jiazhang Key Laboratory of Biomass Chemical Engineering of Ministry of Education State Key Laboratory of Biobased Transportation Fuel Technology College of Chemical and Biological Engineering Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou310000 China

Gene dosage amplification is an effective strategy to improve the performance of heterologous genes and pathways. Pichia pastoris is an excellent recombinant protein expression host with high efficiency in protein folding and glycosylation. However, the traditional iterative multicopy integration method typically faces challenges such as being time-consuming and having high cost and potential gene mutations. Accordingly, we established CRISPR-mediated rDNA integration and fluorescence screening for pathway optimization (CRISPO) for multicopy pathway integration in a single-step and antibiotic-free manner. With geraniol biosynthesis as a case study, we designed CRISPO based on the use of glycerol-induced and glucose-repressed promoters (CRISPOi) or strong constitutive promoters (CRISPOc) to drive the expression of the red fluorescent protein mCherry as the screening marker. We employed CRISPOi for stable strain construction by multicopy integration of the geraniol synthase encoding gene, achieving a 19.5-fold increase in geraniol production. We demonstrated CRISPOc for visualizing and determining the rate-limiting steps of the mevalonate pathway, with HMG1 and ERG12 identified as the major rate-limiting enzymes through two rounds of exploration. Ultimately, CRISPO enabled us to construct an engineered P. pastoris strain producing 1.66 g/L geraniol (with a total of 2.12 g/L monoterpenoids) and 6.27 g/L geraniol (with a total of 6.48 g/L monoterpenoids) in 24-well plates and 5 L fermenters, respectively, representing the highest titer and productivity of geraniol ever reported. CRISPO is an important addition to the synthetic biology toolbox for the construction and optimization of P. pastoris cell factories. © 2024 The Authors. Co-published by Zhejiang University and American Chemical Society.

关键词： Protein folding

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Enhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information 30

Enhancing Cross-Document Event Coreference Resolution by Dis...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Gao, Qiang Li, Bobo Meng, Zixiang Li, Yunlong Zhou, Jun Li, Fei Teng, Chong Ji, Donghong Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University China

ISBN: (纸本)9782493814104

Existing cross-document event coreference resolution models, which either compute mention similarity directly or enhance mention representation by extracting event arguments (such as location, time, agent, and patient), lacking the ability to utilize document-level information. As a result, they struggle to capture long-distance dependencies. This shortcoming leads to their underwhelming performance in determining coreference for the events where their argument information relies on long-distance dependencies. In light of these limitations, we propose the construction of document-level Rhetorical Structure Theory (RST) trees and cross-document Lexical Chains to model the structural and semantic information of documents. Subsequently, cross-document heterogeneous graphs are constructed and GAT is utilized to learn the representations of events. Finally, a pair scorer calculates the similarity between each pair of events and co-referred events can be recognized using standard clustering algorithm. Additionally, as the existing cross-document event coreference datasets are limited to English, we have developed a large-scale Chinese cross-document event coreference dataset to fill this gap, which comprises 53,066 event mentions and 4,476 clusters. After applying our model on the English and Chinese datasets respectively, it outperforms all baselines by large margins. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Clustering algorithms

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Event-Triggered Optimal Nonlinear Systems Control Based on State Observer and Neural Network

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Journal of Systems Science & Complexity 2023年第1期36卷 222-238页

作者： CHENG Songsong LI Haoyun GUO Yuchao PAN Tianhong FAN Yuan Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China

This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time ***,the authors propose an online algorithm with critic and actor NNs to solve the optimal control problem and provide an event-triggered method to reduce communication and computation ***,the authors design weight estimation for critic and actor NNs based on gradient descent method and achieve uniformly ultimate boundednesss(UUB)estimation ***,by using bounded NN weight estimation and dead-zone operator,the authors propose a triggering condition,prove the asymptotic stability of closed-loop system from Lyapunov stability perspective,and exclude the Zeno ***,the authors provide a numerical example to illustrate the effectiveness of the proposed method.

关键词： Event-triggered control neural network optimal control state observer

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Transferable and Robust Dynamic Adversarial Attack against Object Detection Models

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IEEE Internet of Things Journal 2025年第11期12卷 16171-16180页

作者： Wang, Xinxin Chen, Jing Zhang, Zijun He, Kun Wu, Zongru Du, Ruiying Li, Qiao Liu, Gongshen Wuhan University Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan430072 China Shanghai Jiao Tong University Department of Electronic Information and Electrical Engineering Shanghai201100 China

Object detection models have been widely deployed in physical world applications, and they are vulnerable to adversarial attacks. However, most adversarial attacks are implemented in a white-box setting, and under ideal shooting conditions such as fixed distances and angles, and thus have limited attack success rate (ASR) in practice. In this paper, we present a transferable and robust dynamic adversarial attack where the adversarial patches can be printed on or attached to non-rigid objects such as clothes. We develop a cascade module with a momentum-based technique to optimize adversarial patches against various object detection models, achieving better transferability of the patches in a black-box setting. We also develop a strategy of distance-Adaptive patch generation and employ perspective transformation to enhance the robustness of patches. To evaluate the attack performance, we conduct extensive experiments on seven mainstream object detection models at different distances and angles. The results show that our method can achieve an average ASR of 69.85%, which is 3.27 times that of the baseline method at 3 meters. © 2014 IEEE.

关键词： Object detection Computational modeling Closed box Robustness Adaptation models Trusted computing Information security Aerospace engineering Proposals Aerodynamics

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Generating empathetic responses through emotion tracking and constraint guidance

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Frontiers of Computer Science 2024年第2期18卷 243-245页

作者： Jing LI Donghong HAN Zhishuai GUO Baiyou QIAO Gang WU School of Computer Science and Engineering Northeastern UniversityShenyang 110000China Key Laboratory of Intelligent Computing in Medical Image(Ministry of Education) Northeastern UniversityShenyang 110000China Neusoft Corporation Shenyang 110000China

1 Introduction Empathy is an essential human trait,which reflects the ability of understanding and reflecting on the thoughts and feelings of *** empathetic dialogue system can improve user's experience and establishlong-termhuman-machine *** speaker's emotions and predict response's emotions are necessary steps in empathetic dialogue generation.

关键词： interaction. constraint steps

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RRHF-V: Ranking Responses to Mitigate Hallucinations in Multimodal Large Language Models with Human Feedback 31

RRHF-V: Ranking Responses to Mitigate Hallucinations in Mult...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Chen, Guoqing Zhang, Fu Lin, Jinghao Lu, Chenglong Cheng, Jingwei School of Computer Science and Engineering Northeastern University China Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education Northeastern University China

ISBN: (纸本)9798891761964

Multimodal large language models (MLLMs) demonstrate strong capabilities in multimodal understanding, reasoning, and interaction but still face the fundamental limitation of hallucinations, where they generate erroneous or fabricated information. To mitigate hallucinations, existing methods annotate pair-responses (one non-hallucination vs one hallucination) using manual methods or GPT-4V, and train alignment algorithms to improve the correspondence between images and text. More critically, an image description often involve multiple dimensions (e.g., object attributes, posture, and spatial relationships), making it challenging for the model to comprehensively learn multidimensional information from pair-responses. To this end, in this paper, we propose RRHF-V, which is the first using rank-responses (one non-hallucination vs multiple ranking hallucinations) to mitigate multimodal hallucinations. Instead of using pair-responses to train the model, RRHF-V expands the number of hallucinatory responses, so that the responses with different scores in a rank-response enable the model to learn rich semantic information across various dimensions of the image. Further, we propose a scene graph-based approach to automatically construct rank-responses in a cost-effective and automatic manner. We also design a novel training objective based on rank loss and margin loss to balance the differences between hallucinatory responses within a rank-response, thereby improving the model's image comprehension. Experiments on two MLLMs of different sizes and four widely used benchmarks demonstrate that RRHF-V is effective in mitigating hallucinations and outperforms the DPO method based on pair-responses. © 2025 Association for Computational Linguistics.

关键词： Semantics

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Dynamic QoS Mapping and Adaptive Semi-Persistent Scheduling in 5G-TSN Integrated Networks

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China Communications 2023年第4期20卷 340-355页

作者： Yueping Cai Xiaowen Zhang Shaoliu Hu Xiaocong Wei School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400030China Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing UniversityChongqing 400030China

The ubiquitous and deterministic communication systems are becoming indispensable for future vertical applications such as industrial automation systems and smart grids.5G-TSN(Time-Sensitive Networking)integrated networks with the 5G system(5GS)as a TSN bridge are promising to provide the required communication *** guarantee the endto-end(E2E)QoS(Quality of Service)performance of traffic is a great challenge in 5G-TSN integrated networks.A dynamic QoS mapping method is proposed in this *** is based on the improved K-means clustering algorithm and the rough set theory(IKCRQM).The IKC-RQM designs a dynamic and loadaware QoS mapping algorithm to improve its *** adaptive semi-persistent scheduling(ASPS)mechanism is proposed to solve the challenging deterministic scheduling in *** includes two parts:one part is the persistent resource allocation for timesensitive flows,and the other part is the dynamic resource allocation based on the max-min fair share *** results show that the proposed IKC-RQM algorithm achieves flexible and appropriate QoS mapping,and the ASPS performs corresponding resource allocations to guarantee the deterministic transmissions of time-sensitive flows in 5G-TSN integrated networks.

关键词： 5G-TSN integrated networks QoS mapping traffic scheduling resource allocation

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