Check computer science papers: citations, claims and retractions

Designing for Appropriation: A Theoretical Account

Tchounikine, P. (2017) · Human–Computer Interaction

Usability and User Interface DesignInformation Systems Theories and Implementation

Cited by 48

RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors

Dugan, L., Hwang, A., Trhlík, F., Zhu, A., Ludan, J. M., Xu, H., Ippolito, D., & Callison-Burch, C. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Authorship Attribution and ProfilingNatural Language Processing Techniques

Cited by 48

Human Gaze Assisted Artificial Intelligence: A Review

Zhang, R., Saran, A., Liu, B., Zhu, Y., Guo, S., Niekum, S., Ballard, D., & Hayhoe, M. (2020) · Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

Gaze Tracking and Assistive TechnologyVisual Attention and Saliency Detection

Cited by 48

Handling Insider Threat Through Supervised Machine Learning Techniques

Janjua, F., Masood, A., Abbas, H., & Rashid, I. (2020) · Procedia Computer Science

Spam and Phishing DetectionInformation and Cyber Security

Cited by 48

A natural language intelligent tutoring system for training pathologists: implementation and evaluation

El Saadawi, G. M., Tseytlin, E., Legowski, E., Jukic, D., Castine, M., Fine, J., Gormley, R., & Crowley, R. S. (2008) · Advances in Health Sciences Education

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Healthcare and Education

Cited by 48

4D interventional device reconstruction from biplane fluoroscopy

Wagner, M., Schafer, S., Strother, C., & Mistretta, C. (2016) · Medical Physics

Medical Image Segmentation TechniquesRadiation Dose and Imaging

Cited by 48

Parity models: erasure-coded resilience for prediction serving systems

Kosaian, J., Rashmi, K. V., & Venkataraman, S. (2019) · Proceedings of the 27th ACM Symposium on Operating Systems Principles

Distributed systems and fault toleranceCloud Computing and Resource Management

Cited by 48

Private Machine Learning in TensorFlow using Secure Computation

Dahl, M., Mancuso, J., Dupis, Y., Decoste, B., Giraud, M., Livingstone, I., Patriquin, J., & Uhma, G. (2018) · arXiv

Cryptography and Data SecurityPrivacy-Preserving Technologies in Data

Cited by 48

Think2Drive: Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving (in CARLA-v2)

Li, Q., Jia, X., Wang, S., & Yan, J. (2024) · arXiv

Reinforcement Learning in RoboticsAutonomous Vehicle Technology and Safety

Cited by 48

A Dynamic Deep Neural Network Design for Efficient Workload Allocation in Edge Computing

Lo, C., Su, Y.-Y., Lee, C.-Y., & Chang, S.-C. (2017) · 2017 IEEE International Conference on Computer Design (ICCD)

IoT and Edge/Fog ComputingAdvanced Neural Network Applications

Cited by 48

Research on Data Security and Privacy Protection of Wearable Equipment in Healthcare

Jiang, D., & Shi, G. (2021) · Journal of Healthcare Engineering

Internet of Things and AIIoT and Edge/Fog Computing

Cited by 48

A Deep Reinforcement Learning Method for Mobile Robot Collision Avoidance based on Double DQN

Xue, X., Li, Z., Zhang, D., & Yan, Y. (2019) · 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE)

Reinforcement Learning in RoboticsRobotic Path Planning Algorithms

Cited by 48

Development of an agile development method based on Kanban for distributed part-time teams and an introduction framework

Hofmann, C., Lauber, S., Haefner, B., & Lanza, G. (2018) · Procedia Manufacturing

Software Engineering Techniques and PracticesDigital Transformation in Industry

Cited by 48

“Combating deepfakes: multi-LSTM and blockchain as proof of authenticity for digital media,”

Ki Chan, C. C., Kumar, V., Delaney, S., & Gochoo, M. (2020) · 2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)

Digital Media Forensic DetectionBlockchain Technology Applications and Security

Cited by 48

The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performance

Salinas, A., & Morstatter, F. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 48

Support Vector Machines for Anomaly Detection

Zhang, X., Gu, C., & Lin, J. (2006) · 2006 6th World Congress on Intelligent Control and Automation

Anomaly Detection Techniques and ApplicationsNetwork Security and Intrusion Detection

Cited by 48

EPNet: Learning to Exit with Flexible Multi-Branch Network

Dai, X., Kong, X., & Guo, T. (2020) · Proceedings of the 29th ACM International Conference on Information & Knowledge Management

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 48

Real-Time Speech Enhancement Using Equilibriated RNN

Takeuchi, D., Yatabe, K., Koizumi, Y., Oikawa, Y., & Harada, N. (2020) · ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech and Audio ProcessingSpeech Recognition and Synthesis

Cited by 48

AirGPT: Pioneering the convergence of conversational AI with atmospheric science

Song, J., Ma, C., & Ran, M. (2025) · npj Climate and Atmospheric Science

Artificial Intelligence ApplicationsAir Quality Monitoring and Forecasting

Cited by 48

OminiControl: Minimal and Universal Control for Diffusion Transformer

Tan, Z., Liu, S., Yang, X., Xue, Q., & Wang, X. (2025) · 2025 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 48

Leveraging natural language processing to augment structured social determinants of health data in the electronic health record

Lybarger, K., Dobbins, N. J., Long, R., Singh, A., Wedgeworth, P., Uzuner, Ö., & Yetisgen, M. (2023) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 48

Verifiable Anonymous Identities and Access Control in Permissioned Blockchains

Hardjono, T., & Pentland, A. (2019) · arXiv

Blockchain Technology Applications and SecurityCryptography and Data Security

Cited by 48

An Empirical Validation of Malicious Insider Characteristics

Liang, N. (., Biros, D. P., & Luse, A. (2016) · Journal of Management Information Systems

Information and Cyber SecurityCybercrime and Law Enforcement Studies

Cited by 48

A Crawler Architecture for Harvesting the Clear, Social, and Dark Web for IoT-Related Cyber-Threat Intelligence

Koloveas, P., Chantzios, T., Tryfonopoulos, C., & Skiadopoulos, S. (2019) · 2019 IEEE World Congress on Services (SERVICES)

Web Data Mining and AnalysisCybercrime and Law Enforcement Studies

Cited by 48