Check computer science papers: citations, claims and retractions

Sandboxing and Virtualization: Modern Tools for Combating Malware

Greamo, C., & Ghosh, A. (2011) · IEEE Security & Privacy Magazine

Security and Verification in ComputingAdvanced Malware Detection Techniques

Cited by 46

Binders by day, labels by night: effect instances via lexically scoped handlers

Biernacki, D., Piróg, M., Polesiuk, P., & Sieczkowski, F. (2020) · Proceedings of the ACM on Programming Languages

Logic, programming, and type systemsAdvanced Algebra and Logic

Cited by 46

On the Generalization of Deep Learning Models in Video Deepfake Detection

Coccomini, D. A., Caldelli, R., Falchi, F., & Gennaro, C. (2023) · Preprint (MDPI)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 46

Fuzzy cognitive mapping: An old tool with new uses in nursing research

Andersson, N., & Silver, H. (2019) · Journal of Advanced Nursing

Cognitive Science and MappingComplex Systems and Decision Making

Cited by 46

Explainable AI in Industry: Practical Challenges and Lessons Learned

Gade, K., Geyik, S., Kenthapadi, K., Mithal, V., & Taly, A. (2020) · Companion Proceedings of the Web Conference 2020

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 46

Tools to support systematic reviews in software engineering: a cross-domain survey using semi-structured interviews

Marshall, C., Brereton, P., & Kitchenham, B. (2015) · Proceedings of the 19th International Conference on Evaluation and Assessment in Software Engineering

Software Engineering Techniques and PracticesMeta-analysis and systematic reviews

Cited by 46

Explaining Any Time Series Classifier

Guidotti, R., Monreale, A., Spinnato, F., Pedreschi, D., & Giannotti, F. (2020) · 2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI)

Explainable Artificial Intelligence (XAI)Time Series Analysis and Forecasting

Cited by 46

TensorFlow Quantum: Impacts of Quantum State Preparation on Quantum Machine Learning Performance

Sierra-Sosa, D., Telahun, M., & Elmaghraby, A. (2020) · IEEE Access

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 46

Binary Classifier Calibration Using an Ensemble of Near Isotonic Regression Models

Naeini, M. P., & Cooper, G. F. (2016) · 2016 IEEE 16th International Conference on Data Mining (ICDM)

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 46

The case for 4-bit precision: k-bit Inference Scaling Laws

Dettmers, T., & Zettlemoyer, L. (2022) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 46

Direct semi-dense SLAM for rolling shutter cameras

Kim, J.-H., Cadena, C., & Reid, I. (2016) · 2016 IEEE International Conference on Robotics and Automation (ICRA)

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 46

Distilling Object Detectors with Task Adaptive Regularization

Sun, R., Tang, F., Zhang, X., Xiong, H., & Tian, Q. (2020) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 46

Divide and conquer: the role of trust and assurance in the design of secure socio-technical systems

Flechais, I., Riegelsberger, J., & Sasse, M. A. (2005) · Proceedings of the 2005 workshop on New security paradigms - NSPW '05

Information and Cyber SecurityUser Authentication and Security Systems

Cited by 46

Lessons and tips for designing a machine learning study using EHR data

Arbet, J., Brokamp, C., Meinzen-Derr, J., Trinkley, K. E., & Spratt, H. M. (2021) · Journal of Clinical and Translational Science

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 46

Robust principal axes determination for point-based shapes using least median of squares

Liu, Y.-S., & Ramani, K. (2009) · Computer-Aided Design

3D Shape Modeling and AnalysisAdvanced Statistical Methods and Models

Cited by 46

Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study

Tamberg, K., & Bahsi, H. (2024) · arXiv

Software Engineering ResearchWeb Application Security Vulnerabilities

Cited by 46

Scaling Laws of Synthetic Images for Model Training … for Now

Fan, L., Chen, K., Krishnan, D., Katabi, D., Isola, P., & Tian, Y. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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

Cited by 46

Quantum circuits for maximally entangled states

Cervera-Lierta, A., Latorre, J. I., & Goyeneche, D. (2019) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 46

Putting the Horse before the Cart: A Generator-Evaluator Framework for Question Generation from Text

Kumar, V., Ramakrishnan, G., & Li, Y.-F. (2019) · Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)

Topic ModelingNatural Language Processing Techniques

Cited by 46

Exploring Motivators for Trust in the Dichotomy of Human—AI Trust Dynamics

Gerlich, M. (2024) · Social Sciences

Ethics and Social Impacts of AIHuman-Automation Interaction and Safety

Cited by 46

Blockchain-enable Contact Tracing for Preserving User Privacy During COVID-19 Outbreak

Arifeen, M. M., Al Mamun, A., Kaiser, M. S., & Mahmud, M. (2020) · Preprints.org

COVID-19 Digital Contact TracingBlockchain Technology Applications and Security

Cited by 46

Fusion of heart rate variability and pulse rate variability for emotion recognition using lagged poincare plots

Goshvarpour, A., Abbasi, A., & Goshvarpour, A. (2017) · Australasian Physical & Engineering Sciences in Medicine

Emotion and Mood RecognitionHeart Rate Variability and Autonomic Control

Cited by 46

Large language models: an overview of foundational architectures, recent trends, and a new taxonomy

Mienye, I. D., Jere, N., Obaido, G., Ogunruku, O. O., Esenogho, E., & Modisane, C. (2025) · Discover Applied Sciences

Topic ModelingNatural Language Processing Techniques

Cited by 46

Facial expression recognition and emotion classification system for sentiment analysis

Jayalekshmi, J., & Mathew, T. (2017) · 2017 International Conference on Networks & Advances in Computational Technologies (NetACT)

Emotion and Mood RecognitionFace and Expression Recognition

Cited by 46