检索结果-内蒙古大学图书馆

International Symposium on Software Reliability Engineering (ISSRE)

作者： Shenglin Zhang Zeyu Che Zhongjie Pan Xiaohui Nie Yongqian Sun Lemeng Pan Dan Pei Nankai University Haihe Laboratory of Information Technology Application Innovation Computer Network Information Center Chinese Academy of Sciences Tianjin Key Laboratory of Software Experience and Human Computer Interaction Huawei Beijing National Research Center for Information Science and Technology Tsinghua University

ISBN: (数字)9798350353884

ISBN: (纸本)9798350353891

Trace data is crucial for system observability and maintainability within microservices architectures, and many operation algorithms depend heavily on trace data, including anomaly detection, root cause analysis, etc. However, the actual performance of these algorithms might be unsatisfactory due to the absence of high-quality labeled datasets for effective training and evaluation. Since billions of traces could be generated daily for large-scale microservices, labeling overhead is the main hurdle to obtaining high-quality trace *** this paper, we propose LabelEase, a novel semi-automatic trace labeling tool, which uses active learning techniques to achieve efficient and accurate trace labeling. For anomaly trace labeling, LabelEase clusters similar traces with a graph-based trace representation technique and selects a few representative traces for human labeling, avoiding labeling most of the traces. For root cause labeling, LabelEase aggregates the labeled anomalous traces and identifies the service’s failures for operators to label. Our systematic experiments on two large-scale datasets show that LabelEase achieves over 0.98 F 1 -score in anomaly trace labeling and 0.89 precision of failure detection in root cause labeling, LabelEase can reduce operators’ labeling overhead by more than 99.9%. To the best of our knowledge, we are the first to propose a semi-automatic trace labeling tool capable of achieving efficient and accurate trace labeling.

关键词： Training Location awareness Accuracy Costs Transfer learning Microservice architectures Manuals Data models Labeling Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Long-Term Effects of User Expertise and Application Design on Collision Anxiety in VR Games 25

Long-Term Effects of User Expertise and Application Design o...

引用

2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Ring, Patrizia Masuch, Maic Faculty of Computer Science Department of Human-centered Computing and Cognitive Science (HCCS) Entertainment Computing Group University of Duisburg-Essen Duisburg Germany

ISBN: (纸本)9798400713941

Virtual reality (VR) applications achieve their high immersive potential by detaching the user from the real world, replacing it through a virtual environment. This detachment also blocks real-world orientation cues, which might cause fear of colliding with the real environment and negatively impact the player experience. However, since collision anxiety (CA) is a relatively young concept, it is unclear how factors like users' VR expertise or specific game design choices may affect it. We defined expected CA profiles for five commercial VR games and conducted a longitudinal study examining how growing VR expertise and VR game design influence the users' CA. After six weeks and a total of 154 VR sessions, results indicate that CA differs between applications and generally decreases as VR expertise increases. Based on our results, we propose design implications, providing researchers and designers with guidelines on when to expect and how to avoid fear of colliding. © 2025 Copyright held by the owner/author(s).

关键词： assessment collision anxiety discomfort questionnaire spatial orientation user experience user expertise virtual reality VR games VR orientation

来源：评论

学校读者我要写书评

暂无评论

Cueing Sequential 6DoF Rigid-Body Transformations in Augmented Reality

Cueing Sequential 6DoF Rigid-Body Transformations in Augment...

引用

International Symposium on Mixed and Augmented Reality (ISMAR)

作者： Jen-Shuo Liu Barbara Tversky Steven Feiner Department of Computer Science Columbia University Department of Human Development Teachers College Columbia University

Augmented reality (AR) has been used to guide users in multi-step tasks, providing information about the current step (cueing) or future steps (precueing). However, existing work exploring cueing and precueing a series of rigid-body transformations requiring rotation has only examined one-degree-of-freedom (DoF) rotations alone or in conjunction with 3DoF translations. In contrast, we address sequential tasks involving 3DoF rotations and 3DoF translations. We built a testbed to compare two types of visualizations for cueing and precueing steps. In each step, a user picks up an object, rotates it in 3D while translating it in 3D, and deposits it in a target 6DoF pose. Action-based visualizations show the actions needed to carry out a step and goal-based visualizations show the desired end state of a step. We conducted a user study to evaluate these visualizations and the efficacy of precueing. Participants performed better with goal-based visualizations than with action-based visualizations, and most effectively with goal-based visualizations aligned with the Euler axis. However, only a few of our participants benefited from precues, most likely because of the cognitive load of 3D rotations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mitigating Misleading Chain-of-Thought Reasoning with Selective Filtering 30

Mitigating Misleading Chain-of-Thought Reasoning with Select...

引用

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

作者： Wu, Yexin 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

ISBN: (纸本)9782493814104

Large language models have manifested remarkable capabilities by leveraging chain-of-thought (CoT) reasoning techniques to solve intricate questions through step-by-step reasoning chains. Despite its success, the efficacy of such reasoning is inherently contingent upon the quality of CoT. However, flawless CoT reasoning cannot be guaranteed due to the presence of indecomposable questions and the potential for erroneous reasoning chains, particularly in the case of small-scale language models. To tackle this challenge, we propose a novel approach called the selective filtering reasoner (SelF-Reasoner) that assesses the entailment relationship between the question and the candidate reasoning chain. Then, we proceed with CoT reasoning when the reasoning chain demonstrates confidence;otherwise, we opt to predict the answer directly. SelF-Reasoner improves the fine-tuned T5 baseline consistently over the scienceQA, ECQA, and LastLetter tasks. Code is available at https://***/LibroWu/SelF-Reasoner. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Do Text-to-Text Multi-Task Learners Suffer from Task Conflict?

Do Text-to-Text Multi-Task Learners Suffer from Task Conflic...

引用

2022 Findings of the Association for Computational Linguistics: EMNLP 2022

作者： Mueller, David Andrews, Nicholas Dredze, Mark Department of Computer Science Johns Hopkins University United States Human Language Technology Center of Excellence Johns Hopkins University United States

Traditional multi-task learning architectures learn a single model across multiple tasks through a shared encoder followed by task-specific decoders. Learning these models often requires specialized training algorithms that address task-conflict in the shared parameter updates, which otherwise can lead to negative transfer. A new type of multi-task learning within NLP homogenizes multi-task architectures as a shared encoder and language model decoder, which does surprisingly well across a range of diverse tasks (Raffel et al., 2020). Does this new architecture suffer from task-conflicts that require specialized training algorithms? We study how certain factors in the shift towards text-to-text models affects multitask conflict and negative transfer, finding that both directional conflict and transfer are surprisingly constant across architectures. © 2022 Association for Computational Linguistics.

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

Composite Line Designs and Accuracy Measurements for Tactile Line Tracing on Touch Surfaces

引用

Proceedings of the ACM on human-computer interaction 2021年第ISS期5卷 1–17页

作者： Chau, Edwin Yu, Jiakun Goncu, Cagatay Withana, Anusha School of Computer Science The University of Sydney SydneyNSW Australia Department of Human-Centred Computing Monash University MelbourneVIC Australia

Eyes-free operation of mobile devices is critical in situations where the visual channel is either unavailable or attention is needed elsewhere. In such situations, vibrotactile tracing along paths or lines can help users to navigate and identify symbols and shapes without visual information. In this paper, we investigated the applicability of different metrics that can measure the effectiveness of vibrotactile line tracing methods on touch screens. In two user studies, we compare trace Length Error, Area Error, and Fréchet Distance as alternatives to commonly used trace Time. Our results show that a lower Fréchet distance is correlated better with the comprehension of a line trace. Furthermore, we show that distinct feedback methods perform differently with varying geometric features in lines and propose a segmented line design for tactile line tracing studies. We believe the results will inform future designs of eyes-free operation techniques and studies. © 2021 Owner/Author.

关键词： Touch screens

来源：评论

学校读者我要写书评

暂无评论

IoT Implementation in Various Applications: A Detailed Review of Cyber Security Issues and Challenges 3

IoT Implementation in Various Applications: A Detailed Revie...

引用

3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Lourens, Melanie Gangodkar, Durgaprasad Tiwari, Mohit Buddhi, Dharam Dharamvir, Dharamvir Kuchhal, Shikha Durban University of Technology Department of Human Resources Management Durban South Africa Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India Uttaranchal University Uttaranchal Institute of Technology India The Oxford College of Engineering Dept. of Mca Bangalore560068 India Ece Spitm Dcrust India

ISBN: (纸本)9798350399264

Data must be protected against cybercrime as the network revolution grows and becomes more complicated. With the purpose to intentionally damage sensitive and secret information, cybercrimes cost the world economy billions of dollars. Because these crimes are perpetrated often, it is vital to increase cyberspace security to lessen and perhaps even prevent the effects of cybercrime. The internet of things (IoT) phenomena is now the subject of study, as privacy and safety are acknowledged as the primary concerns for Iot., particularly in light of the fact that they are being used in crucial contexts like healthcare systems. The current state of safety in the IoT sector is examined in this paper, along with security-related problems. We look at particular security needs and methods for resolving these problems. IoT safety is being recognised as a problem that blockchains may help with. © 2023 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Instance Regularization for Discriminative Language Model Pre-training

Instance Regularization for Discriminative Language Model Pr...

引用

2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Zhang, Zhuosheng Zhao, Hai Zhou, Ming 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 Langboat Technology

Discriminative pre-trained language models (PrLMs) can be generalized as denoising auto-encoders that work with two procedures, ennoising and denoising. First, an ennoising process corrupts texts with arbitrary noising functions to construct training instances. Then, a denoising language model is trained to restore the corrupted tokens. Existing studies have made progress by optimizing independent strategies of either ennoising or denosing. They treat training instances equally throughout the training process, with little attention on the individual contribution of those instances. To model explicit signals of instance contribution, this work proposes to estimate the complexity of restoring the original sentences from corrupted ones in language model pretraining. The estimations involve the corruption degree in the ennoising data construction process and the prediction confidence in the denoising counterpart. Experimental results on natural language understanding and reading comprehension benchmarks show that our approach improves pre-training efficiency, effectiveness, and robustness. Code is publicly available at https://***/cooelf/InstanceReg. © 2022 Association for Computational Linguistics.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

How Users Who are Blind or Low Vision Play Mobile Games: Perceptions, Challenges, and Strategies 25

How Users Who are Blind or Low Vision Play Mobile Games: Per...

引用

2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Ran, Zihe Li, Xiyu Xiao, Qing Fan, Xianzhe Li, Franklin Mingzhe Wang, Yanyun Lu, Zhicong Communication University of China Beijing China Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States Tsinghua University Beijing China College of Media Communication and Information University of Colorado Boulder Boulder CO United States Department of Computer Science George Mason University Fairfax VA United States

ISBN: (纸本)9798400713941

As blind and low-vision (BLV) players engage more deeply with games, accessibility features have become essential. While some research has explored tools and strategies to enhance game accessibility, the specific experiences of these players with mobile games remain underexamined. This study addresses this gap by investigating how BLV users experience mobile games with varying accessibility levels. Through interviews with 32 experienced BLV mobile players, we explore their perceptions, challenges, and strategies for engaging with mobile games. Our findings reveal that BLV players turn to mobile games to alleviate boredom, achieve a sense of accomplishment, and build social connections, but face barriers depending on the game's accessibility level. We also compare mobile games to other forms of gaming, highlighting the relative advantages of mobile games, such as the inherent accessibility of smartphones. This study contributes to understanding BLV mobile gaming experiences and provides insights for enhancing accessible mobile game design. © 2025 Copyright held by the owner/author(s).

关键词： Blind and Low-Vision (BLV) Users Game Accessibility Global South Mobile Accessibility Mobile Game

来源：评论

学校读者我要写书评

暂无评论

Let's Influence Algorithms Together: How Millions of Fans Build Collective Understanding of Algorithms and Organize Coordinated Algorithmic Actions 25

Let's Influence Algorithms Together: How Millions of Fans Bu...

引用

2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Xiao, Qing Zheng, Yuhang Fan, Xianzhe Zhang, Bingbing Lu, Zhicong Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States University of Amsterdam Amsterdam Amsterdam Netherlands Tsinghua University Beijing China School of Journalism and Mass Communication University of Iowa iowa City IA United States Department of Computer Science George Mason University Fairfax VA United States

ISBN: (纸本)9798400713941

Previous research pays attention to how users strategically understand and consciously interact with algorithms but mainly focuses on an individual level, making it difficult to explore how users within communities could develop a collective understanding of algorithms and organize collective algorithmic actions. Through a two-year ethnography of online fan activities, this study investigates 43 core fans who always organize large-scale fans collective actions and their corresponding general fan groups. This study aims to reveal how these core fans mobilize millions of general fans through collective algorithmic actions. These core fans reported the rhetorical strategies used to persuade general fans, the steps taken to build a collective understanding of algorithms, and the collaborative processes that adapt collective actions across platforms and cultures. Our findings highlight the key factors that enable computer-supported collective algorithmic actions and extend collective action research into the large-scale domain targeting algorithms. © 2025 Copyright held by the owner/author(s).

关键词： Algorithm Collective Algorithmic Action Collective Understanding of Algorithm Fandom Studies Folk Theory of Algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：