Check computer science papers: citations, claims and retractions

Computational thinking in early childhood education: The impact of programming a tangible robot on developing debugging knowledge

Misirli, A., & Komis, V. (2023) · Early Childhood Research Quarterly

Teaching and Learning ProgrammingEducational Robotics and Engineering

Cited by 86

Federated Contrastive Learning With Feature-Based Distillation for Human Activity Recognition

Xiao, Z., & Tong, H. (2025) · IEEE Transactions on Computational Social Systems

Privacy-Preserving Technologies in DataContext-Aware Activity Recognition Systems

Cited by 86

Does GPT-4 pass the Turing test?

Jones, C., & Bergen, B. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 86

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

Wang, J., Hu, X., Hou, W., Chen, H., Zheng, R., Wang, Y., Yang, L., Huang, H., Ye, W., Geng, X., et al. (2023) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 86

Unsupervised Deep Visual-Inertial Odometry with Online Error Correction for RGB-D Imagery

Shamwell, E. J., Lindgren, K., Leung, S., & Nothwang, W. D. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 86

Subpopulation Data Poisoning Attacks

Jagielski, M., Severi, G., Pousette Harger, N., & Oprea, A. (2021) · Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 86

Do Developers Read Compiler Error Messages?

Barik, T., Smith, J., Lubick, K., Holmes, E., Feng, J., Murphy-Hill, E., & Parnin, C. (2017) · 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 86

A survey on moving object tracking using image processing

Balaji, S. R., & Karthikeyan, S. (2017) · 2017 11th International Conference on Intelligent Systems and Control (ISCO)

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 86

A deep-learning model for transforming the style of tissue images from cryosectioned to formalin-fixed and paraffin-embedded

Ozyoruk, K. B., Can, S., Darbaz, B., Başak, K., Demir, D., Gokceler, G. I., Serin, G., Hacisalihoglu, U. P., Kurtuluş, E., Lu, M. Y., et al. (2022) · Nature Biomedical Engineering

AI in cancer detectionGenerative Adversarial Networks and Image Synthesis

Cited by 86

A Review of Embedded Machine Learning Based on Hardware, Application, and Sensing Scheme

Biglari, A., & Tang, W. (2023) · Sensors

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 86

Software security in DevOps: synthesizing practitioners' perceptions and practices

Ur Rahman, A. A., & Williams, L. (2016) · Proceedings of the International Workshop on Continuous Software Evolution and Delivery

Software Engineering Techniques and PracticesWeb Application Security Vulnerabilities

Cited by 86

Protecting against evaluation overfitting in empirical reinforcement learning

Whiteson, S., Tanner, B., Taylor, M. E., & Stone, P. (2011) · 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL)

Reinforcement Learning in RoboticsMachine Learning and Algorithms

Cited by 86

Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk

Barbieri, S., Kemp, J., Perez-Concha, O., Kotwal, S., Gallagher, M., Ritchie, A., & Jorm, L. (2020) · Scientific Reports

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 86

Physiological Linkage of Dyadic Gaming Experience

Järvelä, S., Kivikangas, J. M., Kätsyri, J., & Ravaja, N. (2014) · Simulation & Gaming

Virtual Reality Applications and ImpactsDigital Games and Media

Cited by 86

Profile characteristics of fake Twitter accounts

Gurajala, S., White, J. S., Hudson, B., Voter, B. R., & Matthews, J. N. (2016) · Big Data & Society

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 86

Predicting Phishing Websites Using Classification Mining Techniques with Experimental Case Studies

Aburrous, M., Hossain, M. A., Dahal, K., & Thabtah, F. (2010) · 2010 Seventh International Conference on Information Technology: New Generations

Spam and Phishing DetectionUser Authentication and Security Systems

Cited by 86

DeepLab-Based Spatial Feature Extraction for Hyperspectral Image Classification

Niu, Z., Liu, W., Zhao, J., & Jiang, G. (2019) · IEEE Geoscience and Remote Sensing Letters

Remote-Sensing Image ClassificationAdvanced Image Fusion Techniques

Cited by 86

FairLens: Auditing black-box clinical decision support systems

Panigutti, C., Perotti, A., Panisson, A., Bajardi, P., & Pedreschi, D. (2021) · Information Processing & Management

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 86

MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation

Qian, H., Liu, Z., Zhang, P., Mao, K., Lian, D., Dou, Z., & Huang, T. (2025) · Proceedings of the ACM on Web Conference 2025

Topic ModelingInformation Retrieval and Search Behavior

Cited by 86

Multimodal emotional state recognition using sequence-dependent deep hierarchical features

Barros, P., Jirak, D., Weber, C., & Wermter, S. (2015) · Neural Networks

Emotion and Mood RecognitionSocial Robot Interaction and HRI

Cited by 86

Mix-n-match: Ensemble and compositional methods for uncertainty calibration in deep learning

Zhang, J., Kailkhura, B., & Han, Y.-J. (2020) · Unpublished

Adversarial Robustness in Machine LearningMachine Learning and Data Classification

Cited by 86

Blurring Boundaries in Education: Context and Impact of MOOCs

Loeckx, J. (2016) · The International Review of Research in Open and Distributed Learning

Online Learning and AnalyticsDigital Education and Society

Cited by 86

End-to-end integration of a Convolutional Network, Deformable Parts Model and non-maximum suppression

Wan, L., Eigen, D., & Fergus, R. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 86

Quantum-optimal-control-inspired ansatz for variational quantum algorithms

Choquette, A., Di Paolo, A., Barkoutsos, P. K., Sénéchal, D., Tavernelli, I., & Blais, A. (2021) · Physical Review Research

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 86