Check computer science papers: citations, claims and retractions

Data Governance in the Age of Large-Scale Data-Driven Language Technology

Jernite, Y., Nguyen, H., Biderman, S., Rogers, A., Masoud, M., Danchev, V., Tan, S., Luccioni, A. S., Subramani, N., Johnson, I., et al. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 75

Optimization of inductive RFID technology

Chen, S. C. Q., & Thomas, V. (2002) · Proceedings of the 2001 IEEE International Symposium on Electronics and the Environment. 2001 IEEE ISEE (Cat. No.01CH37190)

RFID technology advancementsWireless Power Transfer Systems

Cited by 75

Less-Forgetful Learning for Domain Expansion in Deep Neural Networks

Jung, H., Ju, J., Jung, M., & Kim, J. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 75

Language Model Crossover: Variation through Few-Shot Prompting

Meyerson, E., Nelson, M. J., Bradley, H., Gaier, A., Moradi, A., Hoover, A. K., & Lehman, J. (2024) · ACM Transactions on Evolutionary Learning and Optimization

Evolutionary Algorithms and ApplicationsTopic Modeling

Cited by 75

Optimizing Agent Behavior over Long Time Scales by Transporting Value

Hung, C.-C., Lillicrap, T., Abramson, J., Wu, Y., Mirza, M., Carnevale, F., Ahuja, A., & Wayne, G. (2018) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 75

Have Learning Analytics Dashboards Lived Up to the Hype? A Systematic Review of Impact on Students' Achievement, Motivation, Participation and Attitude

Kaliisa, R., Misiejuk, K., López-Pernas, S., Khalil, M., & Saqr, M. (2024) · Proceedings of the 14th Learning Analytics and Knowledge Conference

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 75

Augmenting Self-attention with Persistent Memory

Sukhbaatar, S., Grave, E., Lample, G., Jegou, H., & Joulin, A. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 75

Using AI to Teach AI: Lessons from an Online AI Class

Goel, A. K., & Joyner, D. A. (2017) · AI Magazine

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 75

Resource Allocation in Mobility-Aware Federated Learning Networks: A Deep Reinforcement Learning Approach

Nguyen, H. T., Cong Luong, N., Zhao, J., Yuen, C., & Niyato, D. (2020) · 2020 IEEE 6th World Forum on Internet of Things (WF-IoT)

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 75

Towards a holistic framework for multimodal LLM in 3D brain CT radiology report generation

Li, C.-Y., Chang, K.-J., Yang, C.-F., Wu, H.-Y., Chen, W., Bansal, H., Chen, L., Yang, Y.-P., Chen, Y.-C., Chen, S.-P., et al. (2025) · Nature Communications

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 75

Improving human activity recognition and its application in early stroke diagnosis

Villar, J. R., González, S., Sedano, J., Chira, C., & Trejo-Gabriel-Galan, J. M. (2015) · International Journal of Neural Systems

Context-Aware Activity Recognition SystemsArtificial Intelligence in Healthcare

Cited by 75

Towards a context-aware IDE-based meta search engine for recommendation about programming errors and exceptions

Rahman, M. M., Yeasmin, S., & Roy, C. K. (2014) · 2014 Software Evolution Week - IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE)

Software Engineering ResearchInformation Retrieval and Search Behavior

Cited by 75

Combining Machine Learning and Edge Computing: Opportunities, Challenges, Platforms, Frameworks, and Use Cases

Grzesik, P., & Mrozek, D. (2024) · Electronics

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 75

Learning Perfectly Secure Cryptography to Protect Communications with Adversarial Neural Cryptography

Coutinho, M., De Oliveira Albuquerque, R., Borges, F., García Villalba, L., & Kim, T.-H. (2018) · Sensors

Cryptography and Data SecurityCryptographic Implementations and Security

Cited by 75

Enhancing credibility judgment of web search results

Yamamoto, Y., & Tanaka, K. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Information Retrieval and Search BehaviorMisinformation and Its Impacts

Cited by 75

Using deep learning to predict anti-PD-1 response in melanoma and lung cancer patients from histopathology images

Hu, J., Cui, C., Yang, W., Huang, L., Yu, R., Liu, S., & Kong, Y. (2021) · Translational Oncology

AI in cancer detectionCancer Immunotherapy and Biomarkers

Cited by 75

An empirically based model of software prototyping: a mapping study and a multi-case study

Bjarnason, E., Lang, F., & Mjöberg, A. (2023) · Empirical Software Engineering

Software Engineering Techniques and PracticesUsability and User Interface Design

Cited by 75

Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles

Gamper, J., & Rajpoot, N. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

AI in cancer detectionMultimodal Machine Learning Applications

Cited by 75

OmniGen: Unified Image Generation

Xiao, S., Wang, Y., Zhou, J., Yuan, H., Xing, X., Yan, R., Li, C., Wang, S., Huang, T., & Liu, Z. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 75

Imitation Attacks and Defenses for Black-box Machine Translation Systems

Wallace, E., Stern, M., & Song, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 75

Explainable GeoAI: can saliency maps help interpret artificial intelligence’s learning process? An empirical study on natural feature detection

Hsu, C.-Y., & Li, W. (2023) · International Journal of Geographical Information Science

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 75

Enhanced bi-prediction with convolutional neural network for high-efficiency video coding

Zhao, Z., Wang, S., Wang, S., Zhang, X., Ma, S., & Yang, J. (2019) · IEEE Transactions on Circuits and Systems for Video Technology

Video Coding and Compression TechnologiesAdvanced Data Compression Techniques

Cited by 75

Machine learning based feedback on textual student answers in large courses

Bernius, J. P., Krusche, S., & Bruegge, B. (2022) · Computers and Education: Artificial Intelligence

Online Learning and AnalyticsEducational Technology and Assessment

Cited by 75

Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers

Marie, B., Fujita, A., & Rubino, R. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Natural Language Processing Techniquesscientometrics and bibliometrics research

Cited by 75