Check computer science papers: citations, claims and retractions

Predictive Learning in the Presence of Heterogeneity and Limited

Karpatne, A., Khandelwal, A., Boriah, S., & Kumar, V. (2014) · Proceedings of the 2014 SIAM International Conference on Data Mining

Machine Learning and Data ClassificationRemote-Sensing Image Classification

Cited by 25

AI Research Considerations for Human Existential Safety (ARCHES)

Critch, A., & Krueger, D. (2020) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 25

Applying One-Class Algorithms for Data Stream-Based Insider Threat Detection

Peccatiello, R. B., Gondim, J. J. C., & Garcia, L. P. F. (2023) · IEEE Access

Network Security and Intrusion DetectionAnomaly Detection Techniques and Applications

Cited by 25

Explainable AI Evaluation: A Top-Down Approach for Selecting Optimal Explanations for Black Box Models

Mirzaei, S., Mao, H., Al-Nima, R. R. O., & Woo, W. L. (2023) · Information

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 25

Offline Meta-Reinforcement Learning with Online Self-Supervision

Pong, V. H., Nair, A., Smith, L., Huang, C., & Levine, S. (2021) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 25

A principle‐based approach to AI: The case for European Union and Italy

Corea, F., Fossa, F., Loreggia, A., Quintarelli, S., & Sapienza, S. (2023) · AI & SOCIETY

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 25

Online Non-Negative Convolutive Pattern Learning for Speech Signals

Wang, D., Vipperla, R., Evans, N., & Zheng, T. F. (2013) · IEEE Transactions on Signal Processing

Speech and Audio ProcessingSparse and Compressive Sensing Techniques

Cited by 25

Knowledge-Enhanced Language Models Are Not Bias-Proof: Situated Knowledge and Epistemic Injustice in AI

Kraft, A., & Soulier, E. (2024) · The 2024 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIFeminist Epistemology and Gender Studies

Cited by 25

Establishing Trusted I/O Paths for SGX Client Systems With Aurora

Liang, H., Li, M., Chen, Y., Jiang, L., Xie, Z., & Yang, T. (2020) · IEEE Transactions on Information Forensics and Security

Security and Verification in ComputingDigital Rights Management and Security

Cited by 25

Climate Change and Health: The next Challenge of Ethical AI

Fiske, A., Radhuber, I. M., Willem, T., Buyx, A., Celi, L. A., & McLennan, S. (2025) · The Lancet Global Health

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 25

Salience-Guided Iterative Asymmetric Mutual Hashing for Fast Person Re-Identification

Zhao, C., Tu, Y., Lai, Z., Shen, F., Shen, H. T., & Miao, D. (2021) · IEEE Transactions on Image Processing

Video Surveillance and Tracking MethodsAdvanced Image and Video Retrieval Techniques

Cited by 25

“Design and Implementation of Efficient Quantum Support Vector Machine,”

Mafu, M., & Senekane, M. (2021) · 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 25

Generative AI and Power Imbalances in Global Education: Frameworks for Bias Mitigation

Nyaaba, M., Wright, A., & Choi, G. L. (2024) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence in Education

Cited by 25

A transformer-based deep learning approach for fairly predicting post-liver transplant risk factors

Li, C., Jiang, X., & Zhang, K. (2024) · Journal of Biomedical Informatics

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 25

Generalized Hidden Parameter MDPs:Transferable Model-Based RL in a Handful of Trials

Perez, C., Petroski Such, F., & Karaletsos, T. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 25

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control

Xiao, T., Jang, E., Kalashnikov, D., Levine, S., Ibarz, J., Hausman, K., & Herzog, A. (2020) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 25

Intrinsic vs. extrinsic incentives in profit–oriented firms supplying Open Source products and services

Rossi, C., & Bonaccorsi, A. (2005) · First Monday

Open Source Software InnovationsDigital Platforms and Economics

Cited by 25

Training Large Neural Networks with Constant Memory using a New Execution Algorithm

Pudipeddi, B., Mesmakhosroshahi, M., Xi, J., & Bharadwaj, S. (2020) · arXiv

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 25

The effects of online peer-facilitated learning and distributed pair programming on students’ learning

Tsai, C.-W., Lin, M. Y.-C., Cheng, Y.-P., Lee, L.-Y., Chyr, W.-L., Lin, C.-H., Lin, J.-W., & Tsai, M.-C. (2023) · Computers & Education

Teaching and Learning ProgrammingOnline and Blended Learning

Cited by 25

vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation

Wittmann, B., Wattenberg, Y., Amiranashvili, T., Shit, S., & Menze, B. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning

Cited by 25

Preventive Determination and Avoidance of DDoS Attack with SDN over the IoT Networks

Shayshab Azad, K. M., Hossain, N., Islam, M. J., Rahman, A., & Kabir, S. (2021) · 2021 International Conference on Automation, Control and Mechatronics for Industry 4.0 (ACMI)

Network Security and Intrusion DetectionSoftware-Defined Networks and 5G

Cited by 25

“A Comparative Analysis of Automatic Speech Recognition Errors in Small Group Classroom Discourse.”

Cao, J., Ganesh, A., Cai, J., Southwell, R., Perkoff, E. M., Regan, M., Kann, K., Martin, J. H., Palmer, M., & D'Mello, S. (2023) · Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization

Intelligent Tutoring Systems and Adaptive LearningSpeech Recognition and Synthesis

Cited by 25

DeepGA for automatically estimating fetal gestational age through ultrasound imaging

Dan, T., Chen, X., He, M., Guo, H., He, X., Chen, J., Xian, J., Hu, Y., Zhang, B., Wang, N., et al. (2023) · Artificial Intelligence in Medicine

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 25

Simulation of watchdog placement for cooperative anomaly detection in Bluetooth Mesh Intrusion Detection System

Krzysztoń, M., & Marks, M. (2020) · Simulation Modelling Practice and Theory

Network Security and Intrusion DetectionBluetooth and Wireless Communication Technologies

Cited by 25