Check computer science papers: citations, claims and retractions

Quantifying Memorization Across Neural Language Models

Carlini, N., Ippolito, D., Jagielski, M., Lee, K., Tramer, F., & Zhang, C. (2022) · arXiv

Topic ModelingPrivacy-Preserving Technologies in Data

Cited by 204

Multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support

Omar, M., Sorin, V., Collins, J. D., Reich, D., Freeman, R., Gavin, N., Charney, A., Stump, L., Bragazzi, N. L., Nadkarni, G. N., et al. (2025) · Communications Medicine

Adversarial Robustness in Machine LearningArtificial Intelligence in Healthcare and Education

Cited by 204

Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): a retrospective, single-site study

Corey, K. M., Kashyap, S., Lorenzi, E., Lagoo-Deenadayalan, S. A., Heller, K., Whalen, K., Balu, S., Heflin, M. T., McDonald, S. R., Swaminathan, M., et al. (2018) · PLOS Medicine

Machine Learning in HealthcareCardiac, Anesthesia and Surgical Outcomes

Cited by 204

Bandwidth-Efficient Live Video Analytics for Drones Via Edge Computing

Wang, J., Feng, Z., Chen, Z., George, S., Bala, M., Pillai, P., Yang, S.-W., & Satyanarayanan, M. (2018) · 2018 IEEE/ACM Symposium on Edge Computing (SEC)

IoT and Edge/Fog ComputingUAV Applications and Optimization

Cited by 204

Identification of personal traits in adaptive learning environment: Systematic literature review

Afini Normadhi, N. B., Shuib, L., Md Nasir, H. N., Bimba, A., Idris, N., & Balakrishnan, V. (2019) · Computers & Education

Intelligent Tutoring Systems and Adaptive LearningLearning Styles and Cognitive Differences

Cited by 204

Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models

Strobelt, H., Webson, A., Sanh, V., Hoover, B., Beyer, J., Pfister, H., & Rush, A. M. (2022) · arXiv

Topic ModelingData Visualization and Analytics

Cited by 204

Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation With Large Language Models

Strobelt, H., Webson, A., Sanh, V., Hoover, B., Beyer, J., Pfister, H., & Rush, A. M. (2022) · IEEE Transactions on Visualization and Computer Graphics

Topic ModelingData Visualization and Analytics

Cited by 204

Unsupervised MR-to-CT Synthesis Using Structure-Constrained CycleGAN

Yang, H., Sun, J., Carass, A., Zhao, C., Lee, J., Prince, J. L., & Xu, Z. (2020) · IEEE Transactions on Medical Imaging

Generative Adversarial Networks and Image SynthesisMedical Image Segmentation Techniques

Cited by 204

Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction

Kang, S., Yoon, J., & Yoo, S. (2023) · 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 204

Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers.

Moore, J., Grabb, D., Agnew, W., Klyman, K., Chancellor, S., Ong, D. C., & Haber, N. (2025) · Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 204

Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples

Hussain, S., Neekhara, P., Jere, M., Koushanfar, F., & McAuley, J. (2021) · 2021 IEEE Winter Conference on Applications of Computer Vision (WACV)

Digital Media Forensic DetectionAdversarial Robustness in Machine Learning

Cited by 204

A Review of Recent Advances, Challenges, and Opportunities in Malicious Insider Threat Detection Using Machine Learning Methods

Alzaabi, F. R., & Mehmood, A. (2024) · IEEE Access

Information and Cyber SecurityNetwork Security and Intrusion Detection

Cited by 204

Self-Adapting Linear Algebra Algorithms and Software

Demmel, J., Dongarra, J., Eijkhout, V., Fuentes, E., Petitet, A., Vuduc, R., Whaley, R. C., & Yelick, K. (2005) · Proceedings of the IEEE

Matrix Theory and AlgorithmsParallel Computing and Optimization Techniques

Cited by 204

‘Patches don’t have gender’: What is not open in open source software

Nafus, D. (2012) · New Media & Society

Open Source Software InnovationsGender and Technology in Education

Cited by 204

The algorithm audit: Scoring the algorithms that score us

Brown, S., Davidovic, J., & Hasan, A. (2021) · Big Data & Society

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 204

Towards Accurate Generative Models of Video: A New Metric & Challenges

Unterthiner, T., van Steenkiste, S., Kurach, K., Marinier, R., Michalski, M., & Gelly, S. (2018) · arXiv

Generative Adversarial Networks and Image SynthesisArtificial Intelligence in Games

Cited by 204

Multi-institutional validation of a mammography-based breast cancer risk model

Yala, A., Mikhael, P. G., Strand, F., Lin, G., Satuluru, S., Kim, T., Banerjee, I., Gichoya, J., Trivedi, H., Lehman, C. D., et al. (2022) · Journal of Clinical Oncology

AI in cancer detectionDigital Radiography and Breast Imaging

Cited by 204

Unexpected means of protocol inference

Ma, J., Levchenko, K., Kreibich, C., Savage, S., & Voelker, G. M. (2006) · Proceedings of the 6th ACM SIGCOMM conference on Internet measurement

Internet Traffic Analysis and Secure E-votingNetwork Security and Intrusion Detection

Cited by 204

Cross-view image synthesis using conditional GANs

Regmi, K., & Borji, A. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 204

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

Yu, F., Chen, H., Wang, X., Xian, W., Chen, Y., Liu, F., Madhavan, V., & Darrell, T. (2018) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 204

Fault-tolerant quantum computation against biased noise

Aliferis, P., & Preskill, J. (2008) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 204

Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning

Mascharka, D., Tran, P., Soklaski, R., & Majumdar, A. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Explainable Artificial Intelligence (XAI)Multimodal Machine Learning Applications

Cited by 203

Scalable reservoir computing on coherent linear photonic processor

Nakajima, M., Tanaka, K., & Hashimoto, T. (2021) · Communications Physics

Neural Networks and Reservoir ComputingAdvanced Memory and Neural Computing

Cited by 203

Do Prompt-Based Models Really Understand the Meaning of Their Prompts?

Webson, A., & Pavlick, E. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 203