Check computer science papers: citations, claims and retractions

Arabic Cyberbullying Detection: Using Deep Learning

Haidar, B., Chamoun, M., & Serhrouchni, A. (2018) · 2018 7th International Conference on Computer and Communication Engineering (ICCCE)

Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion Mining

Cited by 58

Strategy for Implementing of Zero Trust Architecture

Tsai, M., Lee, S., & Shieh, S. W. (2024) · IEEE Transactions on Reliability

Access Control and TrustInformation and Cyber Security

Cited by 58

Sentiment Classification of Chinese Traveler Reviews by Support Vector Machine Algorithm

Zheng, W., & Ye, Q. (2009) · 2009 Third International Symposium on Intelligent Information Technology Application

Sentiment Analysis and Opinion MiningDigital Marketing and Social Media

Cited by 58

Making sense of sensory input

Evans, R., Hernández-Orallo, J., Welbl, J., Kohli, P., & Sergot, M. (2021) · Artificial Intelligence

AI-based Problem Solving and PlanningBayesian Modeling and Causal Inference

Cited by 58

Diffusion Model as Representation Learner

Yang, X., & Wang, X. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisDomain Adaptation and Few-Shot Learning

Cited by 58

On Activism and Academia: Reflecting Together and Sharing Experiences Among Critical Friends

Leal, D. D. C., Strohmayer, A., & Krüger, M. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AIService-Learning and Community Engagement

Cited by 58

On the Paradox of Learning to Reason from Data

Zhang, H., Li, L. H., Meng, T., Chang, K.-W., & Van den Broeck, G. (2023) · Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence

Topic ModelingLogic, Reasoning, and Knowledge

Cited by 58

Data Quality and Reliability Assessment of Wearable EMG and IMU Sensor for Construction Activity Recognition

Bangaru, S. S., Wang, C., & Aghazadeh, F. (2020) · Sensors

Context-Aware Activity Recognition SystemsMuscle activation and electromyography studies

Cited by 58

A Novel Approach for Rogue Access Point Detection on the Client-Side

Nikbakhsh, S., Manaf, A. B. A., Zamani, M., & Janbeglou, M. (2012) · 2012 26th International Conference on Advanced Information Networking and Applications Workshops

Network Security and Intrusion DetectionWireless Networks and Protocols

Cited by 58

LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers

Olausson, T., Gu, A., Lipkin, B., Zhang, C., Solar-Lezama, A., Tenenbaum, J., & Levy, R. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Logic, Reasoning, and KnowledgeTopic Modeling

Cited by 57

Counting Clicks is Not Enough: Validating a Theorized Model of Engagement in Learning Analytics

Fincham, E., Whitelock-Wainwright, A., Kovanović, V., Joksimović, S., van Staalduinen, J.-P., & Gašević, D. (2019) · Proceedings of the 9th International Conference on Learning Analytics & Knowledge

Online Learning and AnalyticsOnline and Blended Learning

Cited by 57

Pre-processing spectrogram parameters improve the accuracy of bioacoustic classification using convolutional neural networks

Knight, E. C., Poo Hernandez, S., Bayne, E. M., Bulitko, V., & Tucker, B. V. (2020) · Bioacoustics

Music and Audio ProcessingAnimal Vocal Communication and Behavior

Cited by 57

Nested quantum annealing correction

Vinci, W., Albash, T., & Lidar, D. A. (2016) · npj Quantum Information

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 57

ProPILE: Probing Privacy Leakage in Large Language Models

Kim, S., Yun, S., Lee, H., Gubri, M., Yoon, S., & Oh, S. J. (2023) · Advances in Neural Information Processing Systems 36

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 57

An Attention Free Transformer

Zhai, S., Talbott, W., Srivastava, N., Huang, C., Goh, H., Zhang, R., & Susskind, J. (2021) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 57

M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training

Ni, M., Huang, H., Su, L., Cui, E., Bharti, T., Wang, L., Zhang, D., & Duan, N. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 57

Challenges of future multimedia QoE monitoring for internet service providers

Robitza, W., Ahmad, A., Kara, P. A., Atzori, L., Martini, M. G., Raake, A., & Sun, L. (2017) · Multimedia Tools and Applications

Image and Video Quality AssessmentNetwork Traffic and Congestion Control

Cited by 57

Attacks and Preventive Measures on Video Surveillance Systems: A Review

Vennam, P., T. C., P., B. M., T., Kim, Y.-G., & B. N., P. K. (2021) · Applied Sciences

Video Surveillance and Tracking MethodsNetwork Security and Intrusion Detection

Cited by 57

ODD+2D: An ODD Based Protocol for Mapping Data to Empirical ABMs

Laatabi, A., Marilleau, N., Nguyen-Huu, T., Hbid, H., & Ait Babram, M. (2018) · Journal of Artificial Societies and Social Simulation

Multi-Agent Systems and NegotiationSimulation Techniques and Applications

Cited by 57

Automating epistemology: how AI reconfigures truth, authority, and verification

Shin, D. (2026) · AI & SOCIETY

Ethics and Social Impacts of AIMisinformation and Its Impacts

Cited by 57

Probabilistic verification of fairness properties via concentration

Bastani, O., Zhang, X., & Solar-Lezama, A. (2019) · Proceedings of the ACM on Programming Languages

Formal Methods in VerificationEthics and Social Impacts of AI

Cited by 57

“Using a multiplatform chatbot as an online tutor in a university course.”

Lee, L.-K., Fung, Y.-C., Pun, Y.-W., Wong, K.-K., Yu, M. T.-Y., & Wu, N.-I. (2020) · 2020 International Symposium on Educational Technology (ISET)

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 57

An Actionable Framework for Understanding and Improving Developer Experience

Greiler, M., Storey, M.-A., & Noda, A. (2023) · IEEE Transactions on Software Engineering

Software Engineering Techniques and PracticesSoftware Engineering Research

Cited by 57

Driven to Distraction: Self-Supervised Distractor Learning for Robust Monocular Visual Odometry in Urban Environments

Barnes, D., Maddern, W., Pascoe, G., & Posner, I. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA)

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 57