Check computer science papers: citations, claims and retractions

PANDALens: Towards AI-Assisted In-Context Writing on OHMD During Travels

Cai, R., Janaka, N., Chen, Y., Wang, L., Zhao, S., & Liu, C. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionInteractive and Immersive Displays

Cited by 36

One vs. Many: Comprehending Accurate Information from Multiple Erroneous and Inconsistent AI Generations

Lee, Y., Son, K., Kim, T. S., Kim, J., Chung, J. J. Y., Adar, E., & Kim, J. (2024) · The 2024 ACM Conference on Fairness, Accountability, and Transparency

Information Retrieval and Search BehaviorTopic Modeling

Cited by 36

Inference of personality traits and affect schedule by analysis of spontaneous reactions to affective videos

Abadi, M. K., Correa, J. A. M., Wache, J., Yang, H., Patras, I., & Sebe, N. (2015) · 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)

Emotion and Mood RecognitionGaze Tracking and Assistive Technology

Cited by 36

The center for causal discovery of biomedical knowledge from big data

Cooper, G. F., Bahar, I., Becich, M. J., Benos, P. V., Berg, J., Espino, J., Glymour, C., Jacobson, R. C., Kienholz, M., Lee, A. V., et al. (2015) · Journal of the American Medical Informatics Association

Bayesian Modeling and Causal InferencePhilosophy of Biology and Scientific Explanation

Cited by 36

How has forking changed in the last 20 years?: a study of hard forks on GitHub

Zhou, S., Vasilescu, B., & Kästner, C. (2020) · Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering

Open Source Software InnovationsSoftware Engineering Research

Cited by 36

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet

Templeton, A., Conerly, T., Marcus, J., Lindsey, J., Bricken, T., Chen, B., Pearce, A., Citro, C., Ameisen, E., Jones, A., et al. (2026) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 36

A Definition of Continual Reinforcement Learning

Abel, D., Barreto, A., Van Roy, B., Precup, D., van Hasselt, H., & Singh, S. (2023) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 36

Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generation

Becker, B. A., Denny, P., Finnie-Ansley, J., Luxton-Reilly, A., Prather, J., & Santos, E. A. (2022) · arXiv

Teaching and Learning ProgrammingArtificial Intelligence in Education

Cited by 36

Multimodal Emotion Recognition and Sentiment Analysis via Attention Enhanced Recurrent Model

Sun, L., Xu, M., Lian, Z., Liu, B., Tao, J., Wang, M., & Cheng, Y. (2021) · Proceedings of the 2nd on Multimodal Sentiment Analysis Challenge

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 36

Ultra Large-Scale Crowd Monitoring System Architecture and Design Issues

Jiang, Y., Miao, Y., Alzahrani, B., Barnawi, A., Alotaibi, R., & Hu, L. (2021) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingUAV Applications and Optimization

Cited by 36

Machine Interpretation of Emotion: Design of a Memory‐Based Expert System for Interpreting Facial Expressions in Terms of Signaled Emotions

Kearney, G. D., & McKenzie, S. (1993) · Cognitive Science

Emotion and Mood RecognitionFace Recognition and Perception

Cited by 36

Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet

Martínez, G., Watson, L., Reviriego, P., Hernández, J. A., Juarez, M., & Sarkar, R. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisEthics and Social Impacts of AI

Cited by 36

Testing Relational Understanding in Text-Guided Image Generation

Conwell, C., & Ullman, T. (2022) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 36

A visit to the 'new Utopia': revitalizing democracy, emancipation and quality in co-operative design

Iversen, O. S., Kanstrup, A. M., & Petersen, M. G. (2004) · Proceedings of the third Nordic conference on Human-computer interaction

Innovative Human-Technology InteractionInnovative Approaches in Technology and Social Development

Cited by 36

IoT-based platform for environment data sharing in smart cities

Rubí, J. N. S., & de Lira Gondim, P. R. (2021) · International Journal of Communication Systems

IoT and Edge/Fog ComputingSmart Cities and Technologies

Cited by 36

LightSeq: A High Performance Inference Library for Transformers

Wang, X., Xiong, Y., Wei, Y., Wang, M., & Li, L. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers

Topic ModelingNatural Language Processing Techniques

Cited by 36

A Robust Approach for Privacy Data Protection: IoT Security Assurance Using Generative Adversarial Imitation Learning

Huang, C., Chen, S., Zhang, Y., Zhou, W., Rodrigues, J. J. P. C., & de Albuquerque, V. H. C. (2022) · IEEE Internet of Things Journal

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 36

Learning analytics and open, flexible, and distance learning

Siemens, G. (2019) · Distance Education

Online Learning and AnalyticsOnline and Blended Learning

Cited by 36

A Survey of Middleware for Sensor and Network Virtualization

Khalid, Z., Fisal, N., & Rozaini, M. (2014) · Sensors

Energy Efficient Wireless Sensor NetworksWireless Sensor Networks and IoT

Cited by 36

Retrieval-based Spatially Adaptive Normalization for Semantic Image Synthesis

Shi, Y., Liu, X., Wei, Y., Wu, Z., & Zuo, W. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 36

Campus Edge Computing Network Based on IoT Street Lighting Nodes

Chang, Y.-C., & Lai, Y.-H. (2020) · IEEE Systems Journal

IoT and Edge/Fog ComputingEnergy Efficiency in Computing

Cited by 36

Cost-effective detection system of cross-site scripting attacks using hybrid learning approach

Abu Al-Haija, Q. (2023) · Results in Engineering

Web Application Security VulnerabilitiesNetwork Security and Intrusion Detection

Cited by 36

Achieving a data-driven risk assessment methodology for ethical AI

Felländer, A., Rebane, J., Larsson, S., Wiggberg, M., & Heintz, F. (2022) · Digital Society

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 36

FedVision: Federated Video Analytics With Edge Computing

Deng, Y., Han, T., & Ansari, N. (2020) · IEEE Open Journal of the Computer Society

IoT and Edge/Fog ComputingAdvanced Database Systems and Queries

Cited by 36