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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Wei, Yuting Xu, Yuanxing Wei, Xinru Yang, Simin Zhu, Yangfu Li, Yuqing Liu, Di Wu, Bin Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and Telecommunications China

ISBN: (纸本)9798891761681

Given the importance of ancient Chinese in capturing the essence of rich historical and cultural heritage, the rapid advancements in Large Language Models (LLMs) necessitate benchmarks that can effectively evaluate their understanding of ancient contexts. To meet this need, we present AC-EVAL, an innovative benchmark designed to assess the advanced knowledge and reasoning capabilities of LLMs within the context of ancient Chinese. AC-EVAL is structured across three levels of difficulty reflecting different facets of language comprehension: general historical knowledge, short text understanding, and long text comprehension. The benchmark comprises 13 tasks, spanning historical facts, geography, social customs, art, philosophy, classical poetry and prose, providing a comprehensive assessment framework. Our extensive evaluation of top-performing LLMs, tailored for both English and Chinese, reveals a substantial potential for enhancing ancient text comprehension. By highlighting the strengths and weaknesses of LLMs, AC-EVAL aims to promote their development and application forward in the realms of ancient Chinese language education and scholarly research. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Light emission from multiple self-trapped excitons in one-dimensional Ag-based ternary halides

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Chinese Physics B 2024年第11期33卷 62-69页

作者： Jiahao Xie Zewei Li Shengqiao Wang Lijun Zhang State Key Laboratory of Integrated Optoelectronics Key Laboratory of Automobile Materials of MOEKey Laboratory of Material Simulation Methods & Software of MOESchool of Materials Science and EngineeringJilin UniversityChangchun 130000China

Ternary metal halides based on Cu(I)and Ag(I)have attracted intensive attention in optoelectronic applications due to their excellent luminescent properties,low toxicity,and robust *** the self-trapped excitons(STEs)emission mechanisms of Cu(I)halides are well understood,the STEs in Ag(I)halides remain less thoroughly *** study explores the STE emission efficiency within the A_(2)AgX_(3)(A=Rb,Cs;X=Cl,Br,I)system by identifying three distinct STE states in each material and calculating their configuration coordinate *** find that the STE emission efficiency in this system is mainly determined by STE stability and influenced by self-trapping and quenching ***,we investigate the impact of structural compactness on emission efficiency and find that the excessive electron–phonon coupling in this system can be reduced by increasing the structural *** atomic packing factor is identified as a low-cost and effective descriptor for predicting STE emission efficiency in both Cs_(2)AgX_(3) and Rb_(2)AgX_(3) *** findings can deepen our understanding of STE behavior in metal halide materials and offer valuable insights for the design of efficient STE luminescent *** datasets presented in this paper are openly available in Science Data Bank at https://***/10.57760/sciencedb.12094.

关键词： self-trapped exciton Ag-based ternary halides configuration coordinate diagrams emission efficiency

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Bayesian Network Reconstruction and Iterative Divergence Problem Solving Method Based on Norm Minimization

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Computer Modeling in engineering & Sciences 2025年第4期143卷 617-637页

作者： Kuo Li Aimin Wang Limin Wang Yuetan Zhao Xinyu Zhu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun130012China College of Software Jilin UniversityChangchun130012China

A Bayesian network reconstruction method based on norm minimization is proposed to address the sparsity and iterative divergence issues in network reconstruction caused by noise and missing *** method achieves precise adjustment of the network structure by constructing a preliminary random network model and introducing small-world network characteristics and combines L1 norm minimization regularization techniques to control model complexity and optimize the inference process of variable *** the experiment of game network reconstruction,when the success rate of the L1 norm minimization model’s existence connection reconstruction reaches 100%,the minimum data required is about 40%,while the minimum data required for a sparse Bayesian learning network is about 45%.In terms of operational efficiency,the running time for minimizing the L1 normis basically maintained at 1.0 s,while the success rate of connection reconstruction increases significantly with an increase in data volume,reaching a maximum of 13.2 ***,in the case of a signal-to-noise ratio of 10 dB,the L1 model achieves a 100% success rate in the reconstruction of existing connections,while the sparse Bayesian network had the highest success rate of 90% in the reconstruction of non-existent *** the analysis of actual cases,the maximum lift and drop track of the research method is 0.08 *** mean square error is 5.74 cm^(2).The results indicate that this norm minimization-based method has good performance in data efficiency and model stability,effectively reducing the impact of outliers on the reconstruction results to more accurately reflect the actual situation.

关键词： Bayesian norm minimization network reconstruction iterative divergence sparsity

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Robust Multi-UAV Placement Optimization for AOA-Based Cooperative Localization

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年第10期9卷 1-15页

作者： Zhou, Lingyun Ning, Xinzhi You, Ming-Yi Zhang, Rongqing Shi, Qingjiang Department of Hubei Key Laboratory of Intelligent Wireless Communications Hubei Engineering Research Center of Intelligent Internet of Things Technology College of Electronics and Information Engineering South-Central Minzu University Wuhan China School of Software Engineering Tongji University Shanghai China National Key Laboratory of Electromagnetic Space Security No.36 Research Institute of CETC Jiaxing China

Unmanned aerial vehicle (UAV) swarm-based localization technology has become increasingly popular due to its exceptional maneuverability, versatile coverage capabilities, and reliable line-of-sight (LoS) connectivity. However, the accuracy improvement by exploiting UAVs' placement poses a new challenge on multi-UAV localization system. This paper investigates the placement optimization problem for a multi-UAV localization network, where each UAV is equipped with a uniform circular array (UCA) to locate the target by adopting the angle-ofarrival (AOA) measurement. To measure the accuracy of the UCA-based localization system, we characterize the measurement error to be dependent on target-to-UAV distance and present a comprehensive derivation of the Cramer-Rao lower bound ´ (CRLB). Next, we formulate the problem as a non-convex semi-infinite optimization, aiming to minimize the worst-case squared position error bound (SPEB) by designing the robust placement strategy under some stringent geometric position constraints. We address this problem by alternatively solving two sub-problems, corresponding to a slave problem for calculating the worstcase SPEB of the uncertainty region under a fixed deployment of UAVs, as well as a master problem for optimizing UAVs' placement. By virtue of the particular problem structure, we develop the gradient projection-based method for the slave problem. Meanwhile, considering the lack of a closed expression for the maximum SPEB concerning UAVs' deployment in the master problem, we devise an iterative algorithm to acquire an efficient solution with the aid of Gibbs Sampling approach. Extensive simulation results demonstrate the efficacy of the proposed algorithms. IEEE

关键词： Unmanned aerial vehicles (UAV)

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FIFAWC:a dataset with detailed annotation and rich semantics for group activity recognition

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Frontiers of Computer Science 2024年第6期18卷 271-272页

作者： Duoxuan PEI Di HUANG Yunhong WANG State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Intelligent Recognition and Image Processing Lab. School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

1 *** Activity Recognition(GAR),which aims to identify activities performed collectively in videos,has gained significant attention *** conventional action recognition centered on single individuals,GAR explores the c... 详细信息

关键词： has collective gained

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Residual diverse ensemble for long-tailed multi-label text classification

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Science China(Information Sciences) 2024年第11期67卷 92-105页

作者： Jiangxin SHI Tong WEI Yufeng LI National Key Laboratory for Novel Software Technology Nanjing University School of Artificial Intelligence Nanjing University School of Computer Science and Engineering Southeast University Key Laboratory of Computer Network and Information Integration Southeast UniversityMinistry of Education

Long-tailed multi-label text classification aims to identify a subset of relevant labels from a large candidate label set, where the training datasets usually follow long-tailed label distributions. Many of the previous studies have treated head and tail labels equally, resulting in unsatisfactory performance for identifying tail labels. To address this issue, this paper proposes a novel learning method that combines arbitrary models with two steps. The first step is the “diverse ensemble” that encourages diverse predictions among multiple shallow classifiers, particularly on tail labels, and can improve the generalization of tail *** second is the “error correction” that takes advantage of accurate predictions on head labels by the base model and approximates its residual errors for tail labels. Thus, it enables the “diverse ensemble” to focus on optimizing the tail label performance. This overall procedure is called residual diverse ensemble(RDE). RDE is implemented via a single-hidden-layer perceptron and can be used for scaling up to hundreds of thousands of labels. We empirically show that RDE consistently improves many existing models with considerable performance gains on benchmark datasets, especially with respect to the propensity-scored evaluation ***, RDE converges in less than 30 training epochs without increasing the computational overhead.

关键词： multi-label learning extreme multi-label learning long-tailed distribution multi-label text classification ensemble learning

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A Helmet Detection Algorithm Based on Transformers with Deformable Attention Module

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Chinese Journal of Electronics 2025年第1期34卷 229-241页

作者： Songle Chen Hongbo Sun Yuxin Wu Lei Shang Xiukai Ruan Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Nanjing University of Posts and Telecommunications State Key Lab for Novel Software Technology Nanjing University Institute of Intelligent Locks Wenzhou University

Wearing a helmet is one of the effective measures to protect workers' safety. To address the challenges of severe occlusion, multi-scale, and small target issues in helmet detection, this paper proposes a helmet detection algorithm based on deformable attention transformers. The main contributions of this paper are as follows. A compact end-to-end network architecture for safety helmet detection based on transformers is proposed. It cancels the computationally intensive transformer encoder module in the existing detection transformer(DETR) and uses the transformer decoder module directly on the output of feature extraction for query decoding, which effectively improves the efficiency of helmet detection. A novel feature extraction network named Swin transformer with deformable attention module(DSwin transformer) is proposed. By sparse cross-window attention, it enhances the contextual awareness of multi-scale features extracted by Swin transformer, and keeps high computational efficiency simultaneously. The proposed method generates the query reference points and query embeddings based on the joint prediction probabilities, and selects an appropriate number of decoding feature maps and sparse sampling points for query decoding, which further enhance the inference capability and processing speed. On the benchmark safety-helmet-wearing-dataset(SHWD), the proposed method achieves the average detection accuracy mAP@0.5 of 95.4% with 133.35G floating-point operations per second(FLOPs) and 20 frames per second(FPS), the state-of-the-art method for safety helmet detection.

关键词： Head Accuracy Network architecture Benchmark testing Transformers Feature extraction Safety Decoding Computational efficiency Detection algorithms

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Fix the Tests: Augmenting LLMs to Repair Test Cases with Static Collector and Neural Reranker 35

Fix the Tests: Augmenting LLMs to Repair Test Cases with Sta...

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35th IEEE International Symposium on software Reliability engineering, ISSRE 2024

作者： Liu, Jun Yan, Jiwei Xie, Yuanyuan Yan, Jun Zhang, Jian State Key Laboratory of Computer Science Institute of Software China Chinese Academy of Sciences Technology Center of Software Engineering Institute of Software China China UCAS School of Intelligent Science and Technology Hangzhou Institute for Advanced Study China

ISBN: (纸本)9798350353884

During software evolution, it is advocated that test code should co-evolve with production code. In real development scenarios, test updating may lag behind production code changing, which may cause compilation failure or bring other troubles. Existing techniques based on pre-trained language models can be directly adopted to repair obsolete tests caused by such unsynchronized code changes, especially syntactic-related ones. However, the lack of task-oriented contextual information affects the repair accuracy on large-scale projects. Starting from an obsolete test, the key challenging task is precisely identifying and constructing Test-Repair-Oriented Contexts (TROCtxs) from the whole repository within a limited token *** this paper, we propose Synter (SYNtactic-breaking- changes-induced TEst Repair), a novel approach based on LLMs to automatically repair obsolete test cases via precise and concise TROCtxs construction. Inspired by developers' programming practices, we design three types of TROCtx: class context, usage context, and environment context. Given an obsolete test case to repair, Synter firstly collects the related code information for each type of TROCtx through static analysis techniques automatically. Then, it generates reranking queries to identify the most relevant TROCtxs, which will be taken as the repair-required key contexts and be input to the large language model for the final test *** evaluate the effectiveness of Synter, we construct a benchmark dataset that contains a set of obsolete tests caused by syntactic breaking changes. The experimental results show that Synter outperforms baseline approaches both on textual- and intent-matching metrics. With the augmentation of constructed TROCtxs, hallucinations are reduced by 57.1%. © 2024 IEEE.

关键词： Syntactics

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New analytical solutions for free vibration of embedded magneto-electro-elastic cylindrical shells with step-wise thickness variations

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Applied Mathematics and Mechanics(English Edition) 2025年第3期46卷 447-466页

作者： Jufang JIA Huilin YIN Qinyu YU Jiabin SUN Xinsheng XU Zhenhuan ZHOU School of Mechanical Engineering and Automation Dalian Polytechnic UniversityDalian 116034Liaoning ProvinceChina State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentSchool of Mechanics and Aerospace EngineeringDalian University of TechnologyDalian 116024Liaoning ProvinceChina State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentSchool of Chemical EngineeringOcean and Life SciencesDalian University of TechnologyPanjin 124221Liaoning ProvinceChina

In recent years,magneto-electro-elastic(MEE)cylindrical shells with step-wise thicknesses have shown significant potential in the field of vibration energy *** aid the design of such energy harvesting devices,an accurate free vibration analysis of embedded MEE cylindrical shells with step-wise thicknesses is performed within the framework of symplectic *** using the Legendre transformation,a new known vector is defined to transform the higher-order partial differential governing equations into a set of lower-order ordinary differential ***,the original vibration analysis is regarded as an eigen problem in the symplectic space,and analytical solutions can be represented by the symplectic *** numerical examples,the new analytical solutions are compared with the existing results,and good agreement is ***,the effects of critical design parameters on free vibration characteristics are thoroughly *** numerical results can serve as benchmarks for the development of other approximate or numerical methods.

关键词： analytical solution free vibration magneto-electro-elastic(MEE)material cylindrical shell with variable thickness symplectic method

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swSpAMM:optimizing large-scale sparse approximate matrix multiplication on Sunway Taihulight

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Frontiers of Computer Science 2023年第4期17卷 29-41页

作者： Xiaoyan LIU Yi LIU Bohong YIN Hailong YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China

Although matrix multiplication plays an essential role in a wide range of applications,previous works only focus on optimizing dense or sparse matrix *** Sparse Approximate Matrix Multiply(SpAMM)is an algorithm to accelerate the multiplication of decay matrices,the sparsity of which is between dense and sparse *** addition,large-scale decay matrix multiplication is performed in scientific applications to solve cutting-edge *** optimize large-scale decay matrix multiplication using SpAMM on supercomputers such as Sunway Taihulight,we present swSpAMM,an optimized SpAMM algorithm by adapting the computation characteristics to the architecture features of Sunway ***,we propose both intra-node and inter-node optimizations to accelerate swSpAMM for large-scale *** intra-node optimizations,we explore algorithm parallelization and block-major data layout that are tailored to better utilize the architecture advantage of Sunway *** inter-node optimizations,we propose a matrix organization strategy for better distributing sub-matrices across nodes and a dynamic scheduling strategy for improving load balance across *** compare swSpAMM with the existing GEMM library on a single node as well as large-scale matrix multiplication methods on multiple *** experiment results show that swSpAMM achieves a speedup up to 14.5×and 2.2×when compared to xMath library on a single node and 2D GEMM method on multiple nodes,respectively.

关键词： approximate calculation sunway processor performance optimization

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