Check computer science papers: citations, claims and retractions

Virtual worlds vs books and videos in history education

Ijaz, K., Bogdanovych, A., & Trescak, T. (2017) · Interactive Learning Environments

Virtual Reality Applications and ImpactsAugmented Reality Applications

Cited by 106

What Makes Good In-Context Demonstrations for Code Intelligence Tasks with LLMs?

Gao, S., Wen, X.-C., Gao, C., Wang, W., Zhang, H., & Lyu, M. R. (2023) · 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)

Software Engineering ResearchTopic Modeling

Cited by 106

The derivative ratio algorithm: avoiding atmospheric effects in remote sensing.

Philpot, W. D. (1991) · IEEE Transactions on Geoscience and Remote Sensing

Remote-Sensing Image ClassificationRemote Sensing and Land Use

Cited by 106

Beyond generalization: a theory of robustness in machine learning

Freiesleben, T., & Grote, T. (2023) · Synthese

Adversarial Robustness in Machine LearningExplainable Artificial Intelligence (XAI)

Cited by 106

Benchmarking the performance of portfolio optimization with QAOA

Brandhofer, S., Braun, D., Dehn, V., Hellstern, G., Hüls, M., Ji, Y., Polian, I., Bhatia, A. S., & Wellens, T. (2022) · Quantum Information Processing

Quantum Computing Algorithms and ArchitectureRisk and Portfolio Optimization

Cited by 106

Face Forgery Detection by 3D Decomposition

Zhu, X., Wang, H., Fei, H., Lei, Z., & Li, S. Z. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionFace recognition and analysis

Cited by 106

Near or far? It depends on my impression: Moral information and spatial behavior in virtual interactions

Iachini, T., Pagliaro, S., & Ruggiero, G. (2015) · Acta Psychologica

Virtual Reality Applications and ImpactsEmbodied and Extended Cognition

Cited by 106

Toward the neural implementation of structure learning

Tervo, D. G. R., Tenenbaum, J. B., & Gershman, S. J. (2016) · Current Opinion in Neurobiology

Bayesian Modeling and Causal InferenceMemory and Neural Mechanisms

Cited by 106

Adaptive feedback from artificial neural networks facilitates pre-service teachers’ diagnostic reasoning in simulation-based learning

Sailer, M., Bauer, E., Hofmann, R., Kiesewetter, J., Glas, J., Gurevych, I., & Fischer, F. (2023) · Learning and Instruction

Intelligent Tutoring Systems and Adaptive LearningStudent Assessment and Feedback

Cited by 106

Inertial measurements of upper limb motion

Zhou, H., Hu, H., & Tao, Y. (2006) · Medical & Biological Engineering & Computing

Context-Aware Activity Recognition SystemsStroke Rehabilitation and Recovery

Cited by 106

Meta Reinforcement Learning with Latent Variable Gaussian Processes

Sæmundsson, S., Hofmann, K., & Deisenroth, M. P. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 106

The social honeypot project: protecting online communities from spammers

Lee, K., Caverlee, J., & Webb, S. (2010) · Proceedings of the 19th international conference on World wide web

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 106

Machine learning in infection management using routine electronic health records: Tools, techniques, and reporting of future technologies

Luz, C. F., Vollmer, M., Decruyenaere, J., Nijsten, M. W., Glasner, C., & Sinha, B. (2020) · Clinical Microbiology and Infection

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 106

Overcoming the bootstrap problem in evolutionary robotics using behavioral diversity

Mouret, J.-B., & Doncieux, S. (2009) · 2009 IEEE Congress on Evolutionary Computation

Evolutionary Algorithms and ApplicationsModular Robots and Swarm Intelligence

Cited by 106

Free lunch for testing: fuzzing deep-learning libraries from open source

Wei, A., Deng, Y., Yang, C., & Zhang, L. (2022) · Proceedings of the 44th International Conference on Software Engineering

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 106

Does Explainable Artificial Intelligence Improve Human Decision-Making?

Alufaisan, Y., Marusich, L. R., Bakdash, J. Z., Zhou, Y., & Kantarcioglu, M. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 106

Personalized input: improving ten-finger touchscreen typing through automatic adaptation

Findlater, L., & Wobbrock, J. (2012) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignInteractive and Immersive Displays

Cited by 106

Reassessing automatic evaluation metrics for code summarization tasks

Roy, D., Fakhoury, S., & Arnaoudova, V. (2021) · Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Software Engineering ResearchNatural Language Processing Techniques

Cited by 106

6G white paper: Research challenges for trust, security and privacy

Ylianttila, M., Kantola, R., Gurtov, A., Mucchi, L., Oppermann, I., Yan, Z., Nguyen, T. H., Liu, F., Hewa, T., Liyanage, M., et al. (2020) · arXiv

Cybersecurity and Information SystemsSoftware-Defined Networks and 5G

Cited by 106

Data Carpentry: Workshops to Increase Data Literacy for Researchers

Teal, T. K., Cranston, K. A., Lapp, H., White, E., Wilson, G., Ram, K., & Pawlik, A. (2015) · International Journal of Digital Curation

Research Data Management PracticesScientific Computing and Data Management

Cited by 106

Superhuman artificial intelligence can improve human decision-making by increasing novelty

Shin, M., Kim, J., van Opheusden, B., & Griffiths, T. L. (2023) · Proceedings of the National Academy of Sciences

Artificial Intelligence in GamesArtificial Intelligence Applications

Cited by 106

The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers

Csordás, R., Irie, K., & Schmidhuber, J. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 106

Anomaly Detection using Graph Neural Networks

Chaudhary, A., Mittal, H., & Arora, A. (2019) · 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon)

Anomaly Detection Techniques and ApplicationsComplex Network Analysis Techniques

Cited by 106

An Energy-Efficient Networking Approach in Cloud Services for IIoT Networks

Jiang, D., Wang, Y., Lv, Z., Wang, W., & Wang, H. (2020) · IEEE Journal on Selected Areas in Communications

Cloud Computing and Resource ManagementEnergy Efficiency in Computing

Cited by 106