ACM Computing Surveys最新文献_第4页

Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey 近10年来视觉任务的对抗性攻击研究综述

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-06 DOI: 10.1145/3743126

Chiyu Zhang, Lu Zhou, Xiaogang Xu, Jiafei Wu, Zhe Liu

引用次数: 0

RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs 破译RLHF: llm从人类反馈中强化学习的关键分析

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-05 DOI: 10.1145/3743127

Shreyas Chaudhari, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, Ameet Deshpande, Bruno Castro da Silva

引用次数: 0

Towards Message Brokers for Generative AI: Survey, Challenges, and Opportunities 面向生成人工智能的消息代理：调查、挑战和机遇

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-05 DOI: 10.1145/3742891

Alaa Saleh, Roberto Morabito, Schahram Dustdar, Sasu Tarkoma, Susanna Pirttikangas, Lauri Lovén

{"title":"Towards Message Brokers for Generative AI: Survey, Challenges, and Opportunities","authors":"Alaa Saleh, Roberto Morabito, Schahram Dustdar, Sasu Tarkoma, Susanna Pirttikangas, Lauri Lovén","doi":"10.1145/3742891","DOIUrl":"https://doi.org/10.1145/3742891","url":null,"abstract":"In today’s digital world, GenAI is becoming increasingly prevalent by enabling unparalleled content generation capabilities for a wide range of advanced applications. This surge in adoption has sparked a significant increase in demand for data-centric GenAI models spanning the distributed edge-cloud continuum, placing increasing demands on communication infrastructures, highlighting the necessity for robust communication solutions. Central to this need are message brokers, which serve as essential channels for data transfer within various system components. This survey aims to delve into a comprehensive analysis of traditional and modern message brokers based on a variety of criteria, highlighting their critical role in enabling efficient data exchange in distributed AI systems. Furthermore, we explore the intrinsic constraints that the design and operation of each message broker might impose, highlighting their impact on real-world applicability. Finally, this study explores the enhancement of message broker mechanisms tailored to GenAI environments. It considers key factors such as scalability, semantic communication, and distributed inference that can guide future innovations and infrastructure advancements in the realm of GenAI data communication.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"25 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graph Deep Learning for Time Series Forecasting 图深度学习用于时间序列预测

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-03 DOI: 10.1145/3742784

Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi

{"title":"Graph Deep Learning for Time Series Forecasting","authors":"Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi","doi":"10.1145/3742784","DOIUrl":"https://doi.org/10.1145/3742784","url":null,"abstract":"Graph deep learning methods have become popular tools to process collections of correlated time series. Unlike traditional multivariate forecasting methods, graph-based predictors leverage pairwise relationships by conditioning forecasts on graphs spanning the time series collection. The conditioning takes the form of architectural inductive biases on the forecasting architecture, resulting in a family of models called spatiotemporal graph neural networks. These biases allow for training global forecasting models on large collections of time series while localizing predictions w.r.t. each element in the set (nodes) by accounting for correlations among them (edges). Recent advances in graph neural networks and deep learning for time series forecasting make the adoption of such processing framework appealing and timely. However, most studies focus on refining existing architectures by exploiting modern deep-learning practices. Conversely, foundational and methodological aspects have not been subject to systematic investigation. To fill this void, this tutorial paper aims to introduce a comprehensive methodological framework formalizing the forecasting problem and providing design principles for graph-based predictors, as well as methods to assess their performance. In addition, together with an overview of the field, we provide design guidelines and best practices, as well as an in-depth discussion of open challenges and future directions.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"41 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Benchmarking Relaxed Differential Privacy in Private Learning: A Comparative Survey 私教学习中放松差别隐私的基准：一项比较调查

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-03 DOI: 10.1145/3729216

Zhaolong Zheng, Lin Yao, Haibo Hu, Guowei Wu

{"title":"Benchmarking Relaxed Differential Privacy in Private Learning: A Comparative Survey","authors":"Zhaolong Zheng, Lin Yao, Haibo Hu, Guowei Wu","doi":"10.1145/3729216","DOIUrl":"https://doi.org/10.1145/3729216","url":null,"abstract":"Differential privacy (DP), a rigorously quantifiable privacy preservation technique, has found widespread application within the domain of machine learning. As DP techniques are implemented in machine learning algorithms, a significant and intricate trade-off between privacy and utility emerges, garnering extensive attention from researchers. In the pursuit of striking a delicate equilibrium between safeguarding sensitive data and optimizing its utility, researchers have introduced various variants of Relaxed Differential Privacy (RDP) definitions. These nuanced formulations, however, exhibit substantial diversity in their underlying principles and interpretations of the core concept of DP, thereby engendering a current void in the comprehensive synthesis of these related works. The principal objective of this article is twofold. Firstly, it aims to provide a comprehensive summary of pertinent research endeavors pertaining to RDP within the realm of machine learning. Secondly, it endeavors to empirically assess the impact on both privacy and utility stemming from machine learning algorithms founded upon these RDP definitions. Additionally, this article undertakes a systematic analysis of the foundational principles underpinning distinct variants of relaxed definitions, culminating in the development of a taxonomy that categorizes these RDP definitions.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"8 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey on Employing Large Language Models for Text-to-SQL Tasks 文本转sql任务中使用大型语言模型的研究

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-03 DOI: 10.1145/3737873

Liang Shi, Zhengju Tang, Nan Zhang, Xiaotong Zhang, Zhi Yang

引用次数: 0

A Survey of Program Analysis for Distributed Software Systems 分布式软件系统程序分析综述

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-03 DOI: 10.1145/3742900

Haipeng Cai

{"title":"A Survey of Program Analysis for Distributed Software Systems","authors":"Haipeng Cai","doi":"10.1145/3742900","DOIUrl":"https://doi.org/10.1145/3742900","url":null,"abstract":"Distributed software systems are pervasive today and they are increasingly developed/deployed to meet the growing needs for scalable computing. Given their critical roles in modern information infrastructures, assuring the quality of distributed software is crucial. As a fundamental methodology for software quality assurance in general, program analysis underlies a range of techniques and tools for constructing and assuring distributed systems. Yet to this date there remains a lack of systematical understandings of what have been done and how far we are in the field of program analysis for distributed systems. To gain a comprehensive and coherent view of this area hence inform relevant future research, this paper provides a systematic literature review of the (1) technical approaches , including analysis methodology, modality, underlying representation, algorithmic design, data utilized, and scope, (2) applications , with respect to the quality aspects served, and (3) evaluation , including the datasets and metrics considered, of various program analyses in the domain of distributed software in the past 30 years (1995–2024). In addition to knowledge systematization, we also extend our insights into the limitations of and challenges faced by current technique and evaluation designs, which shed light on potentially promising future research directions .","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"31 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating EEG Microstate Analysis in Cognitive Software Engineering Tasks: A Systematic Mapping Study and Taxonomy 认知软件工程任务中的脑电微状态分析研究：系统映射研究与分类

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-03 DOI: 10.1145/3742899

Willian Bolzan, Kleinner Farias

{"title":"Investigating EEG Microstate Analysis in Cognitive Software Engineering Tasks: A Systematic Mapping Study and Taxonomy","authors":"Willian Bolzan, Kleinner Farias","doi":"10.1145/3742899","DOIUrl":"https://doi.org/10.1145/3742899","url":null,"abstract":"Performing software engineering (SE) tasks requires the activation of software developers’ brain neural networks. Electroencephalography (EEG) microstate analysis emerges as a promising neurophysiological method to investigate the spatiotemporal dynamics of brain networks at high temporal resolution. An EEG microstate represents a unique topography of electric potentials over the multichannel EEG records. However, academia has neglected classifying published studies on EEG microstate analysis related to SE. Hence, a careful understanding of state-of-the-art studies remains limited and inconclusive. This article aims to classify studies on the EEG microstate analysis in cognitive SE tasks. We conducted a systematic mapping study following well-established guidelines to answer ten research questions. After careful filtering, 54 primary studies (out of 1.545) were selected from 8 electronic databases. The main results are that most primary studies focus on revealing brain dynamics, exploring a wide range of EEG microstate application contexts and experimental tasks, running empirical studies in a controlled environment, using K-means as a clustering method, applying ICA-based strategy to filter artifacts, such as muscle activity and eye blinks. However, No study has applied EEG microstate analysis to SE, highlighting a significant gap and the need for further research. Finally, this article presents a classification taxonomy and identifies critical challenges and future research directions.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"62 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Survey on Factuality in Large Language Models 大型语言模型中的事实性研究

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-06-02 DOI: 10.1145/3742420

Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, Qipeng Guo, Xiangkun Hu, Xiangru Tang, Tianhang Zhang, Cheng Jiayang, Yunzhi Yao, Xuming Hu, Zehan Qi, Wenyang Gao, Yidong Wang, Linyi Yang, Jindong Wang, Xing Xie, Zheng Zhang, Yue Zhang

引用次数: 0

An End-to-End Pipeline Perspective on Video Streaming in Best-Effort Networks: A Survey and Tutorial 在最努力的网络中视频流的端到端管道视角：调查和教程

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2025-05-31 DOI: 10.1145/3742472

Leonardo Peroni, Sergey Gorinsky

{"title":"An End-to-End Pipeline Perspective on Video Streaming in Best-Effort Networks: A Survey and Tutorial","authors":"Leonardo Peroni, Sergey Gorinsky","doi":"10.1145/3742472","DOIUrl":"https://doi.org/10.1145/3742472","url":null,"abstract":"Remaining a dominant force in Internet traffic, video streaming captivates end users, service providers, and researchers. This paper takes a pragmatic approach to reviewing recent advances in the field by focusing on the prevalent streaming paradigm that involves delivering long-form two-dimensional videos over the best-effort Internet with client-side adaptive bitrate (ABR) algorithms and assistance from content delivery networks (CDNs). To enhance accessibility, we supplement the survey with tutorial material. Unlike existing surveys that offer fragmented views, our work provides a holistic perspective on the entire end-to-end streaming pipeline, from video capture by a camera-equipped device to playback by the end user. Our novel perspective covers the ingestion, processing, and distribution stages of the pipeline and addresses key challenges such as video compression, upload, transcoding, ABR algorithms, CDN support, and quality of experience. We review over 200 papers and classify streaming designs by problem-solving methodology, whether based on intuition, theory, or machine learning. The survey further refines these methodology-based categories and characterizes each design by additional traits such as compatible codecs. We connect the reviewed research to real-world applications by discussing the practices of commercial streaming platforms. Finally, the survey highlights prominent current trends and outlines future directions in video streaming.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"38 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144189017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0