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Judicial nested named entity recognition method with MRC framework

International Journal of Cognitive Computing in Engineering 2023年第1期4卷 118-126页

作者： Zhang, Hu Guo, Jiayu Wang, Yujie Zhang, Zhen Zhao, Hansen School of Computer and Information Technology Shanxi University Shanxi Taiyuan030006 China Department of Computation Science and Engineering George Institute of Technology Atlanta United States

Judicial named entity recognition (JNER) is a basic task of judicial intelligence and judicial service informatization. At present, the research of JNER has attracted extensive attention. However, the existing JNER methods usually can only assign a single label to a token in the input sequence, which is not applicable to nested entities where a token may be assigned two or more different labels at the same time. Therefore, this paper introduces the machine reading comprehension (MRC) framework into JNER, and proposes a judicial nested NER method based on the MRC. Firstly, we design the question template according to the characteristics of judicial nested named entities, and construct the legal text named entity dataset in MRC format. Next, we introduce the span extraction MRC model based on the pre-trained to encode the question and text, and learn the context knowledge of the entity in the question. Finally, we extract the starting and end positions of the matching span respectively through two classifiers, to get the corresponding entities. The experimental results on the information extraction dataset in "CAIL2021" show, compared with the existing baseline models, the proposed method effectively improves the recognition effect of nested entities commonly existing in the judicial field. © 2023

关键词： Informatization

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Mixed-decomposed convolutional network:A lightweight yet efficient convolutional neural network for ocular disease recognition

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CAAI Transactions on Intelligence technology 2024年第2期9卷 319-332页

作者： Xiaoqing Zhang Xiao Wu Zunjie Xiao Lingxi Hu Zhongxi Qiu Qingyang Sun Risa Higashita Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhenChina Tomey Corporation NagoyaJapan Guangdong Provincial Key Laboratory of Brain‐inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhenChina Singapore Eye Research Institute SingaporeSingapore

Eye health has become a global health concern and attracted broad *** the years,researchers have proposed many state-of-the-art convolutional neural networks(CNNs)to assist ophthalmologists in diagnosing ocular diseases efficiently and ***,most existing methods were dedicated to constructing sophisticated CNNs,inevitably ignoring the trade-off between performance and model *** alleviate this paradox,this paper proposes a lightweight yet efficient network architecture,mixeddecomposed convolutional network(MDNet),to recognise ocular *** MDNet,we introduce a novel mixed-decomposed depthwise convolution method,which takes advantage of depthwise convolution and depthwise dilated convolution operations to capture low-resolution and high-resolution patterns by using fewer computations and fewer *** conduct extensive experiments on the clinical anterior segment optical coherence tomography(AS-OCT),LAG,University of California San Diego,and CIFAR-100 *** results show our MDNet achieves a better trade-off between the performance and model complexity than efficient CNNs including MobileNets and ***,our MDNet outperforms MobileNets by 2.5%of accuracy by using 22%fewer parameters and 30%fewer computations on the AS-OCT dataset.

关键词： artificial intelligence deep learning deep neural networks image analysis image classification medical applications medical image processing

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Generalized Unique Reconstruction From Substrings

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IEEE Transactions on Information Theory 2023年第9期69卷 5648-5659页

作者： Yehezkeally, Yonatan Bar-Lev, Daniella Marcovich, Sagi Yaakobi, Eitan Institute for Communications Engineering School of ComputationInformation and Technology Technical University of Munich Munich80333 Germany Department of Computer Science Technion-Israel Institute of Technology Haifa3200003 Israel

This paper introduces a new family of reconstruction codes which is motivated by applications in DNA data storage and sequencing. In such applications, DNA strands are sequenced by reading some subset of their substrings. While previous works considered two extreme cases in which all substrings of pre-defined lengths are read or substrings are read with no overlap for the single string case, this work studies two extensions of this paradigm. The first extension considers the setup in which consecutive substrings are read with some given minimum overlap. First, an upper bound is provided on the attainable rates of codes that guarantee unique reconstruction. Then, efficient constructions of codes that asymptotically meet that upper bound are presented. In the second extension, we study the setup where multiple strings are reconstructed together. Given the number of strings and their length, we first derive a lower bound on the read substrings' length that is necessary for the existence of multi-strand reconstruction codes with non-vanishing rates. We then present two constructions of such codes and show that their rates approach 1 for values of that asymptotically behave like the lower bound. © 2023 IEEE.

关键词： Digital storage

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DEEPSPF: SPHERICAL SO(3)-EQUIVARIANT PATCHES FOR SCAN-TO-CAD ESTIMATION 12

DEEPSPF: SPHERICAL SO(3)-EQUIVARIANT PATCHES FOR SCAN-TO-CAD...

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12th International Conference on Learning Representations, ICLR 2024

作者： Salihu, Driton Misik, Adam Wu, Yuankai Patsch, Constantin Seguel, Fabian Steinbach, Eckehard Munich Institute of Robotics and Machine Intelligence Department of Computer Engineering Technical University of Munich School of Computation Information and Technology Germany Siemens Technology Germany

Recently, SO(3)-equivariant methods have been explored for 3D reconstruction via Scan-to-CAD. Despite significant advancements attributed to the unique characteristics of 3D data, existing SO(3)-equivariant approaches often fall short in seamlessly integrating local and global contextual information in a widely generalizable manner. Our contributions in this paper are threefold. First, we introduce Spherical Patch Fields, a representation technique designed for patch-wise, SO(3)-equivariant 3D point clouds, anchored theoretically on the principles of Spherical Gaussians. Second, we present the Patch Gaussian Layer, designed for the adaptive extraction of local and global contextual information from resizable point cloud patches. Culminating our contributions, we present Learnable Spherical Patch Fields (DeepSPF) - a versatile and easily integrable backbone suitable for instance-based point networks. Through rigorous evaluations, we demonstrate significant enhancements in Scan-to-CAD performance for point cloud registration, retrieval, and completion: a significant reduction in the rotation error of existing registration methods, an improvement of up to 17% in the Top-1 error for retrieval tasks, and a notable reduction of up to 30% in the Chamfer Distance for completion models, all attributable to the incorporation of DeepSPF. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： computer aided design

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An Improved Method for Class-specific Keyword Extraction: A Case Study in the German Business Registry 20

An Improved Method for Class-specific Keyword Extraction: A ...

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20th Conference on Natural Language Processing, KONVENS 2024

作者： Meisenbacher, Stephen Schopf, Tim Yan, Weixin Holl, Patrick Matthes, Florian Technical University of Munich School of Computation Information and Technology Department of Computer Science Garching Germany Fusionbase GmbH Munich Germany

The task of keyword extraction is often an important initial step in unsupervised information extraction, forming the basis for tasks such as topic modeling or document classification. While recent methods have proven to be quite effective in the extraction of keywords, the identification of class-specific keywords, or only those pertaining to a predefined class, remains challenging. In this work, we propose an improved method for class-specific keyword extraction, which builds upon the popular KEYBERT library to identify only keywords related to a class described by seed keywords. We test this method using a dataset of German business registry entries, where the goal is to classify each business according to an economic sector. Our results reveal that our method greatly improves upon previous approaches, setting a new standard for class-specific keyword extraction. ©2024 Association for computational Linguistics.

关键词： computational linguistics

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How Can CoPs in Scaled Agile Settings Look Like? Toward a Taxonomy for CoPs in Large-Scale Agile Software Development 58

How Can CoPs in Scaled Agile Settings Look Like? Toward a Ta...

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58th Hawaii International Conference on System Sciences, HICSS 2025

作者： Tobisch, Franziska Schmidt, Johannes Matthes, Florian Technical University of Munich School of Computation Information and Technology Department of Computer Science Garching Germany

ISBN: (纸本)9780998133188

Fast-changing business environments and customer needs require organizations to react quickly and adapt to changes. While agile software development methods can support organizations in achieving this goal, applying these methods in a large context, like multi-team projects, entails high complexity. Several scaling agile frameworks recommend Communities of Practice (CoP), groups of people with a shared interest that exchange with each other on a regular basis, to support the application of agile at scale, as they can foster, e.g., inter-team collaboration and alignment. Still, no clear overview of aspects that must be considered when establishing and cultivating CoPs in scaled agile settings exists. Therefore, we propose a taxonomy for CoPs in this context, building on literature and findings of an interview study. The taxonomy can support practitioners and researchers, offering a structured overview of aspects relevant to establishing and cultivating CoPs in large-scale agile settings and future research directions. © 2025 IEEE computer Society. All rights reserved.

关键词： Software design

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Self-Attention Based Action Segmentation Using Intra-And Inter-Segment Representations 48

Self-Attention Based Action Segmentation Using Intra-And Int...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Patsch, Constantin Steinbach, Eckehard Technical University of Munich School of Computation Information and Technology Germany Chair of Media Technology Department of Computer Engineering Germany

ISBN: (纸本)9781728163277

Segmenting activities in untrimmed videos remains a critical challenge to fully understand complex human activity sequences. A correct representation of temporal action relations is key for improving incorrect segmentations. We propose a self-attention-based model that refines initial segmentations by separately considering intra-as well as inter-segment relations between predicted action segments. Furthermore, in order to enhance the training process, we use a similarity-guided regularization technique that ensures intra-segment similarity and the validity of action transitions between adjacent segments. In an extensive evaluation on three public datasets -Georgia Tech Egocentric Activities, 50Salads, and Breakfast -our proposed architecture enhances the backbone model by 6.1% on GTEA, 3.8% on 50Salads, and 3.9% on Breakfast with regard to the F 1@50 metric. © 2023 IEEE.

关键词： computer vision

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Multithreaded parallelism for heterogeneous clusters of QPUs 39

Multithreaded parallelism for heterogeneous clusters of QPUs

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39th International Conference on High Performance Computing, ISC High Performance 2024

作者： Seitz, Philipp Geiger, Manuel Mendl, Christian B. Technical University of Munich TUM School of Computation Information and Technology Department of Computer Science Boltzmannstraße 3 Garching85748 Germany Technical University of Munich TUM School of Computation Information and Technology Department of Computer Science TUM Institute for Advanced Study Boltzmannstraße 3 Garching85748 Germany

ISBN: (纸本)9783982633602

In this work, we present MILQ, a quantum unrelated parallel machines scheduler and cutter. The setting of unrelated parallel machines considers independent hardware backends, each distinguished by differing setup and processing times. MILQ optimizes the total execution time of a batch of circuits scheduled on multiple quantum devices. It leverages state-of-the-art circuit-cutting techniques to fit circuits onto the devices and schedules them based on a mixed-integer linear program. Our results show a total improvement of up to 26 % compared to a baseline approach. © 2024 Research Paper Proceedings of the ISC High Performance 2024. All rights reserved.

关键词： Integer programming

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Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care Environments

Care3D: An Active 3D Object Detection Dataset of Real Roboti...

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2023 IEEE International Symposium on Multimedia, ISM 2023

作者： Adam, Michael G. Eger, Sebastian Piccolrovazzi, Martin Iskandar, Maged Vogel, Joern Dietrich, Alexander Bien, Seongjien Skerlj, Jon Naceri, Abdeldjallil Steinbach, Eckehard Albu-Schaeffer, Alin Haddadin, Sami Burgard, Wolfram Technical University of Munich Media Technology Department of Computer Engineering School of Computation Information and Technology Munich Germany Wessling Germany Robotics and Systems Intelligence Department of Computer Engineering School of Computation Information and Technology Technical University of Munich Munich Germany University of Technology Nuremberg Engineering Department Nuremberg Germany

ISBN: (纸本)9798350395761

As labor shortage increases in the health sector, the demand for assistive robotics grows. However, the needed test data to develop those robots is scarce, especially for the application of active 3D object detection, where no real data exists at all. This short paper counters this by introducing such an annotated dataset of real environments. The captured environments represent areas which are already in use in the field of robotic health care research. We further provide ground truth data within one room, for assessing SLAM algorithms running directly on a health care robot. © 2023 IEEE.

关键词： Object detection

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Visual Explanations of Some Problematic Search Behaviors of Frequently-Used EMO Algorithms 13th

Visual Explanations of Some Problematic Search Behaviors of ...

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13th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2025

作者： Ishibuchi, Hisao Pang, Lie Meng Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9789819635375

Recently, evolutionary multi-objective optimization (EMO) algorithms have been used in various application fields. Whereas many new EMO algorithms are proposed every year, well-known EMO algorithms such as NSGA-II, MOEA/D, SMS-EMOA and NSGA-III have been still frequently used in application papers as shown by their number of citations. Since most EMO algorithms have been designed for and evaluated by artificial test problems such as DTLZ and WFG, they do not always work well on real-world problems. Main difficulties of real-world problems are as follows: (i) their Pareto front shapes are irregular, (ii) some objectives have much larger values than others, (iii) some decision variables have much larger values than others, (iv) some objectives are highly correlated, and (v) solution evaluation is expensive. In this paper, we focus on the first four difficulties (except for expensive solution evaluation). Our goal is to clearly explain problematic search behaviors of NSGA-II, MOEA/D, SMS-EMOA and NSGA-III caused by these difficulties using simple distance minimization problems. We formulate various distance minimization problems with the above-mentioned four difficulties by changing the location of each target point on the map as well as the size and shape of the map. We also suggest simple remedies for performance improvement of each algorithm for real-world applications without changing the algorithm itself. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

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