Check computer science papers: citations, claims and retractions

Akamai DNS: Providing Authoritative Answers to the World's Queries

Schomp, K., Bhardwaj, O., Kurdoglu, E., Muhaimen, M., & Sitaraman, R. K. (2020) · Proceedings of the Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication

Caching and Content DeliverySoftware System Performance and Reliability

Cited by 38

Sim-to-Real Transfer with Incremental Environment Complexity for Reinforcement Learning of Depth-based Robot Navigation

Chaffre, T., Moras, J., Chan-Hon-Tong, A., & Marzat, J. (2020) · Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 38

Efficient image encryption scheme with synchronous substitution and diffusion based on double S-boxes

Zhang, X.-P., Guo, R., Chen, H.-W., Zhao, Z.-M., & Wang, J.-Y. (2018) · Chinese Physics B

Chaos-based Image/Signal EncryptionCryptographic Implementations and Security

Cited by 38

OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations

Ouyang, L., Qu, Y., Zhou, H., Zhu, J., Zhang, R., Lin, Q., Wang, B., Zhao, Z., Jiang, M., Zhao, X., et al. (2024) · arXiv

Handwritten Text Recognition TechniquesInformation Systems and Technology Applications

Cited by 38

Threats and Defenses in the Federated Learning Life Cycle: A Comprehensive Survey and Challenges

Li, Y., Guo, Z., Yang, N., Chen, H., Yuan, D., & Ding, W. (2025) · IEEE Transactions on Neural Networks and Learning Systems

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 38

Navigating software development in the ChatGPT and GitHub copilot era

France, S. L. (2024) · Business Horizons

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 38

Intraoperative stent segmentation in X-ray fluoroscopy for endovascular aortic repair

Breininger, K., Albarqouni, S., Kurzendorfer, T., Pfister, M., Kowarschik, M., & Maier, A. (2018) · International Journal of Computer Assisted Radiology and Surgery

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 38

Towards AI-Assisted Synthesis of Verified Dafny Methods

Misu, M. R. H., Lopes, C. V., Ma, I., & Noble, J. (2024) · Proceedings of the ACM on Software Engineering

Logic, programming, and type systemsSoftware Engineering Research

Cited by 38

Explaining deep learning-based anomaly detection in energy consumption data by focusing on contextually relevant data

Noorchenarboo, M., & Grolinger, K. (2025) · Energy and Buildings

Explainable Artificial Intelligence (XAI)Anomaly Detection Techniques and Applications

Cited by 38

Augmented reality in cultural heritage: Field of view awareness in an archaeological site mobile guide

Kasapakis, V., Gavalas, D., & Galatis, P. (2016) · Journal of Ambient Intelligence and Smart Environments

Augmented Reality ApplicationsInteractive and Immersive Displays

Cited by 38

Multi-Faceted Recall of Continuous Active Learning for Technology-Assisted Review

Cormack, G. V., & Grossman, M. R. (2015) · Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval

Information Retrieval and Search BehaviorMachine Learning and Algorithms

Cited by 38

Mixed Precision Training With 8-bit Floating Point

Mellempudi, N., Srinivasan, S., Das, D., & Kaul, B. (2019) · arXiv

Numerical Methods and AlgorithmsAdvanced Neural Network Applications

Cited by 38

Predicting next-day discharge via electronic health record access logs

Zhang, X., Yan, C., Malin, B. A., Patel, M. B., & Chen, Y. (2021) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 38

Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models

Zhou, K., Jurafsky, D., & Hashimoto, T. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 38

Trustworthy agentic AI systems: a cross-layer review of architectures, threat models, and governance strategies for real-world deployment

ADABARA, I., Olaniyi Sadiq, B., Nuhu Shuaibu, A., Ibrahim Danjuma, Y., & Maninti, V. (2025) · F1000Research

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 38

Differentiable Learning-to-Group Channels via Groupable Convolutional Neural Networks

Zhang, Z., Li, J., Shao, W., Peng, Z., Zhang, R., Wang, X., & Luo, P. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 38

An efficient edge artificial intelligence multipedestrian tracking method with rank constraint

Yang, H., Wen, J., Wu, X., He, L., & Mumtaz, S. (2019) · IEEE Transactions on Industrial Informatics

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 38

Online grooming detection: A comprehensive survey of child exploitation in chat logs

Borj, P. R., Raja, K., & Bours, P. (2023) · Knowledge-Based Systems

Authorship Attribution and ProfilingHate Speech and Cyberbullying Detection

Cited by 38

Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs

Zantedeschi, V., Bellet, A., & Tommasi, M. (2019) · arXiv

Privacy-Preserving Technologies in DataDistributed Control Multi-Agent Systems

Cited by 38

Enhancing precision in detecting severe immune-related adverse events: comparative analysis of large language models and international classification of disease codes in patient records

Sun, V. H., Heemelaar, J. C., Hadzic, I., Raghu, V. K., Wu, C.-Y., Zubiri, L., Ghamari, A., LeBoeuf, N. R., Abu-Shawer, O., Kehl, K. L., et al. (2024) · Journal of Clinical Oncology

Machine Learning in HealthcareCancer Immunotherapy and Biomarkers

Cited by 38

Particle filtering for registration of 2D and 3D point sets with stochastic dynamics

Sandhu, R., Dambreville, S., & Tannenbaum, A. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition

3D Shape Modeling and AnalysisTarget Tracking and Data Fusion in Sensor Networks

Cited by 38

Towards Probabilistic Verification of Machine Unlearning

Sommer, D. M., Song, L., Wagh, S., & Mittal, P. (2020) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 38

From local counterfactuals to global feature importance: efficient, robust, and model-agnostic explanations for brain connectivity networks

Alfeo, A. L., Zippo, A. G., Catrambone, V., Cimino, M. G. C. A., Toschi, N., & Valenza, G. (2023) · Computer Methods and Programs in Biomedicine

Explainable Artificial Intelligence (XAI)Functional Brain Connectivity Studies

Cited by 38

Energetic Cost of Superadiabatic Quantum Computation

Coulamy, I. B., Santos, A. C., Hen, I., & Sarandy, M. S. (2016) · Frontiers in ICT

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 38