Check computer science papers: citations, claims and retractions

Modeling the structural relationship among primary students’ motivation to learn artificial intelligence

Lin, P.-Y., Chai, C.-S., Jong, M. S.-Y., Dai, Y., Guo, Y., & Qin, J. (2021) · Computers and Education: Artificial Intelligence

Teaching and Learning ProgrammingEducation, Achievement, and Giftedness

Cited by 171

A multimodal whole-slide foundation model for pathology

Ding, T., Wagner, S. J., Song, A. H., Chen, R. J., Lu, M. Y., Zhang, A., Vaidya, A. J., Jaume, G., Shaban, M., Kim, A., et al. (2025) · Nature Medicine

AI in cancer detectionMultimodal Machine Learning Applications

Cited by 171

Everyday Algorithm Auditing: Understanding the Power of Everyday Users in Surfacing Harmful Algorithmic Behaviors

Shen, H., DeVos, A., Eslami, M., & Holstein, K. (2021) · Proceedings of the ACM on Human-Computer Interaction

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 171

Personal Informatics, Self-Insight, and Behavior Change: A Critical Review of Current Literature

Kersten-van Dijk, E. T., Westerink, J. H. D. M., Beute, F., & IJsselsteijn, W. A. (2017) · Human–Computer Interaction

Innovative Human-Technology InteractionMobile Health and mHealth Applications

Cited by 171

FairTest: Discovering Unwarranted Associations in Data-Driven Applications

Tramèr, F., Atlidakis, V., Geambasu, R., Hsu, D., Hubaux, J.-P., Humbert, M., Juels, A., & Lin, H. (2015) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 171

Quantum reservoir processing

Ghosh, S., Opala, A., Matuszewski, M., Paterek, T., & Liew, T. C. H. (2019) · npj Quantum Information

Neural Networks and Reservoir ComputingQuantum Computing Algorithms and Architecture

Cited by 171

Abstracting log lines to log event types for mining software system logs

Nagappan, M., & Vouk, M. A. (2010) · 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)

Software System Performance and ReliabilitySoftware Engineering Research

Cited by 171

Quantifying the Impact of Edge Computing on Mobile Applications

Hu, W., Gao, Y., Ha, K., Wang, J., Amos, B., Chen, Z., Pillai, P., & Satyanarayanan, M. (2016) · Proceedings of the 7th ACM SIGOPS Asia-Pacific Workshop on Systems

IoT and Edge/Fog ComputingMobile and Web Applications

Cited by 171

On Low-Resolution Face Recognition in the Wild: Comparisons and New Techniques

Li, P., Prieto, L., Mery, D., & Flynn, P. J. (2019) · IEEE Transactions on Information Forensics and Security

Face recognition and analysisFace and Expression Recognition

Cited by 171

Insights on representational similarity in neural networks with canonical correlation

Morcos, A. S., Raghu, M., & Bengio, S. (2018) · arXiv

Neural Networks and ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 171

Tutorial on specialisation of logic programs

Gallagher, J. P. (1993) · Proceedings of the 1993 ACM SIGPLAN symposium on Partial evaluation and semantics-based program manipulation - PEPM '93

Logic, programming, and type systemsLogic, Reasoning, and Knowledge

Cited by 171

TensorFlow-Serving: Flexible, High-Performance ML Serving

Olston, C., Fiedel, N., Gorovoy, K., Harmsen, J., Lao, L., Li, F., Rajashekhar, V., Ramesh, S., & Soyke, J. (2017) · arXiv

Cloud Computing and Resource ManagementAdvanced Neural Network Applications

Cited by 171

An elephant in the learning analytics room: the obligation to act

Prinsloo, P., & Slade, S. (2017) · Proceedings of the Seventh International Learning Analytics & Knowledge Conference

Online Learning and AnalyticsEducational and Technological Research

Cited by 171

Cryptanalyzing and improving a novel color image encryption algorithm using RT-enhanced chaotic tent maps

Zhu, C., & Sun, K. (2018) · IEEE Access

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 171

Alleviating Over-segmentation Errors by Detecting Action Boundaries

Ishikawa, Y., Kasai, S., Aoki, Y., & Kataoka, H. (2021) · 2021 IEEE Winter Conference on Applications of Computer Vision (WACV)

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 171

Extracting all the randomness and reducing the error in Trevisan's extractors

Raz, R., Reingold, O., & Vadhan, S. (1999) · Proceedings of the thirty-first annual ACM symposium on Theory of Computing

Computability, Logic, AI AlgorithmsCoding theory and cryptography

Cited by 171

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

Liu, B., Zhu, C., Li, G., Zhang, W., Lai, J., Tang, R., He, X., Li, Z., & Yu, Y. (2020) · Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 171

Pix2Video: Video Editing using Image Diffusion

Ceylan, D., Huang, C.-H. P., & Mitra, N. J. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 171

Detection, classification and tracking of moving objects in a 3D environment

Azim, A., & Aycard, O. (2012) · 2012 IEEE Intelligent Vehicles Symposium

Robotics and Sensor-Based LocalizationAutonomous Vehicle Technology and Safety

Cited by 171

MLPerf: An Industry Standard Benchmark Suite for Machine Learning Performance

Mattson, P., Reddi, V. J., Cheng, C., Coleman, C., Diamos, G., Kanter, D., Micikevicius, P., Patterson, D., Schmuelling, G., Tang, H., et al. (2020) · IEEE Micro

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 171

Progressive Neural Architecture Search

Liu, C., Zoph, B., Neumann, M., Shlens, J., Hua, W., Li, L.-J., Fei-Fei, L., Yuille, A., Huang, J., & Murphy, K. (2017) · arXiv

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 171

Evading Deepfake-Image Detectors with White- and Black-Box Attacks

Carlini, N., & Farid, H. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Digital Media Forensic DetectionAdversarial Robustness in Machine Learning

Cited by 170

Predictive Modeling of the Hospital Readmission Risk from Patients’ Claims Data Using Machine Learning: A Case Study on COPD

Min, X., Yu, B., & Wang, F. (2019) · Scientific Reports

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 170

Iterative Qubit Coupled Cluster Approach with Efficient Screening of Generators

Ryabinkin, I. G., Lang, R. A., Genin, S. N., & Izmaylov, A. F. (2020) · Journal of Chemical Theory and Computation

Quantum Computing Algorithms and ArchitectureAdvanced Chemical Physics Studies

Cited by 170