Check computer science papers: citations, claims and retractions

VLAAD: Vision and Language Assistant for Autonomous Driving

Park, S., Lee, M., Kang, J., Choi, H., Park, Y., Cho, J., Lee, A., & Kim, D. (2024) · 2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)

Multimodal Machine Learning ApplicationsAutonomous Vehicle Technology and Safety

Cited by 49

Mitigating the Backdoor Attack by Federated Filters for Industrial IoT Applications

Hou, B., Gao, J., Guo, X., Baker, T., Zhang, Y., Wen, Y., & Liu, Z. (2022) · IEEE Transactions on Industrial Informatics

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 49

Prototyping nfv-based multi-access edge computing in 5G ready networks with open baton

Carella, G. A., Pauls, M., Magedanz, T., Cilloni, M., Bellavista, P., & Foschini, L. (2017) · 2017 IEEE Conference on Network Softwarization (NetSoft)

Software-Defined Networks and 5GIoT and Edge/Fog Computing

Cited by 49

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Anuoluwapo, A., Bosselut, A., Chandu, K. R., Clinciu, M., Das, D., Dhole, K. D., et al. (2021) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 49

Management of Wireless Communication Systems Using Artificial Intelligence-Based Software Defined Radio

Bargarai, F. A. M., Abdulazeez, A. M., Tiryaki, V. M., & Zeebaree, D. Q. (2020) · International Journal of Interactive Mobile Technologies (iJIM)

Cognitive Radio Networks and Spectrum SensingAdvanced Wireless Network Optimization

Cited by 49

IS AI GROUND TRUTH REALLY TRUE? THE DANGERS OF TRAINING AND EVALUATING AI TOOLS BASED ON EXPERTS’ KNOW-WHAT.

Lebovitz, S., Levina, N., & Lifshitz-Assaf, H. (2021) · MIS Quarterly

Artificial Intelligence ApplicationsInformation Systems Theories and Implementation

Cited by 49

A framework for evaluating automatic indexing or classification in the context of retrieval

Golub, K., Soergel, D., Buchanan, G., Tudhope, D., Lykke, M., & Hiom, D. (2016) · Journal of the Association for Information Science and Technology

Information Retrieval and Search BehaviorLibrary Science and Information Systems

Cited by 49

Mac-layer packet loss models for wi-fi networks: A survey

Silva, C. A. G. D., & Pedroso, C. M. (2019) · IEEE Access

Wireless Networks and ProtocolsNetwork Traffic and Congestion Control

Cited by 49

Remote digital measurement of facial and vocal markers of major depressive disorder severity and treatment response: a pilot study

Abbas, A., Sauder, C., Yadav, V., Koesmahargyo, V., Aghjayan, A., Marecki, S., Evans, M., & Galatzer-Levy, I. R. (2021) · Frontiers in Digital Health

Emotion and Mood RecognitionTreatment of Major Depression

Cited by 49

Dependable integrated surveillance systems for the physical security of metro railways

Bocchetti, G., Flammini, F., & Pappalardo, A. (2009) · 2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)

Video Surveillance and Tracking MethodsTechnology and Security Systems

Cited by 49

Overlap in meaning is a stronger predictor of semantic activation in GPT-3 than in humans

Digutsch, J., & Kosinski, M. (2023) · Scientific Reports

Topic ModelingNeurobiology of Language and Bilingualism

Cited by 49

SoK: A Study of Using Hardware-assisted Isolated Execution Environments for Security

Zhang, F., & Zhang, H. (2016) · Proceedings of the Hardware and Architectural Support for Security and Privacy 2016

Security and Verification in ComputingDistributed systems and fault tolerance

Cited by 49

Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers

Gao, Y., Long, Y., Guan, Y., Basu, A., Baggaley, J., & Ploetz, T. (2019) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Context-Aware Activity Recognition SystemsNeonatal and fetal brain pathology

Cited by 49

Mariana: tencent deep learning platform and its applications

Zou, Y., Jin, X., Li, Y., Guo, Z., Wang, E., & Xiao, B. (2014) · Proceedings of the VLDB Endowment

Parallel Computing and Optimization TechniquesCloud Computing and Resource Management

Cited by 49

Natural Language to Code Translation with Execution

Shi, F., Fried, D., Ghazvininejad, M., Zettlemoyer, L., & Wang, S. I. (2022) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 49

Fine-grained Hallucination Detection and Editing for Language Models

Mishra, A., Asai, A., Balachandran, V., Wang, Y., Neubig, G., Tsvetkov, Y., & Hajishirzi, H. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 49

Enabling deep learning at the IoT edge

Lai, L., & Suda, N. (2018) · Proceedings of the International Conference on Computer-Aided Design

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 49

The Performance of Post-Quantum TLS 1.3

Sosnowski, M., Wiedner, F., Hauser, E., Steger, L., Schoinianakis, D., Gallenmüller, S., & Carle, G. (2023) · Companion of the 19th International Conference on emerging Networking EXperiments and Technologies

Cryptography and Residue ArithmeticCryptography and Data Security

Cited by 49

IoT Quality Control for Data and Application Needs

Banerjee, T., & Sheth, A. (2017) · IEEE Intelligent Systems

Internet of Things and AIIoT and Edge/Fog Computing

Cited by 49

Different Approaches to Assessing the Quality of Explanations Following a Multiple-Document Inquiry Activity in Science

Wiley, J., Hastings, P., Blaum, D., Jaeger, A. J., Hughes, S., Wallace, P., Griffin, T. D., & Britt, M. A. (2017) · International Journal of Artificial Intelligence in Education

Intelligent Tutoring Systems and Adaptive LearningScience Education and Pedagogy

Cited by 49

Generative AI in Game Design: Enhancing Creativity or Constraining Innovation?

Alharthi, S. A. (2025) · Journal of Intelligence

Artificial Intelligence in GamesDigital Media and Visual Art

Cited by 49

A novel ensemble of deep learning approach for cybersecurity intrusion detection with explainable artificial intelligence

Alabdulatif, A. (2025) · Applied Sciences

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 49

MedGemma Technical Report

Sellergren, A., Kazemzadeh, S., Jaroensri, T., Kiraly, A., Traverse, M., Kohlberger, T., Xu, S., Jamil, F., Hughes, C., Lau, C., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 49

Software defined networking firewall for industry 4.0 manufacturing systems

Tsuchiya, A., Fraile, F., Koshijima, I., Ortiz, A., & Poler, R. (2018) · Journal of Industrial Engineering and Management

Software-Defined Networks and 5GNetwork Security and Intrusion Detection

Cited by 49