Check computer science papers: citations, claims and retractions

Benchmarking machine learning models on multi-centre eICU critical care dataset

Sheikhalishahi, S., Balaraman, V., & Osmani, V. (2020) · PLOS ONE

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 89

The Generative Adversarial Brain

Gershman, S. J. (2019) · Frontiers in Artificial Intelligence

Neural Networks and ApplicationsBayesian Modeling and Causal Inference

Cited by 89

SoK: Everyone Hates Robocalls: A Survey of Techniques Against Telephone Spam

Tu, H., Doupe, A., Zhao, Z., & Ahn, G.-J. (2016) · 2016 IEEE Symposium on Security and Privacy (SP)

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 89

Analyzing Multimodal Sentiment Via Acoustic- and Visual-LSTM With Channel-Aware Temporal Convolution Network

Mai, S., Xing, S., & Hu, H. (2021) · IEEE/ACM Transactions on Audio, Speech, and Language Processing

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 89

Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning

Yarats, D., Fergus, R., Lazaric, A., & Pinto, L. (2021) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 89

Authorship Attribution with Topic Models

Seroussi, Y., Zukerman, I., & Bohnert, F. (2014) · Computational Linguistics

Authorship Attribution and ProfilingTopic Modeling

Cited by 89

Investigating novice programming mistakes: educator beliefs vs. student data

Brown, N. C. C., & Altadmri, A. (2014) · Proceedings of the tenth annual conference on International computing education research

Teaching and Learning ProgrammingSoftware Engineering Research

Cited by 89

How "Quantum" is the D-Wave Machine?

Shin, S. W., Smith, G., Smolin, J. A., & Vazirani, U. (2014) · arXiv

Quantum Computing Algorithms and ArchitectureParallel Computing and Optimization Techniques

Cited by 89

Fast and converged classical simulations of evidence for the utility of quantum computing before fault tolerance

Begušić, T., Gray, J., & Chan, G. K.-L. (2024) · Science Advances

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 89

Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes

Rae, J. W., Hunt, J. J., Harley, T., Danihelka, I., Senior, A., Wayne, G., Graves, A., & Lillicrap, T. P. (2016) · arXiv

Neural Networks and ApplicationsTopic Modeling

Cited by 89

Big Data, Big Problems: Emerging Issues in the Ethics of Data Science and Journalism

Fairfield, J., & Shtein, H. (2014) · Journal of Mass Media Ethics

Ethics and Social Impacts of AIJournalism and Media Studies

Cited by 89

Comparative evaluation of autocontouring in clinical practice: A practical method using the Turing test

Gooding, M. J., Smith, A. J., Tariq, M., Aljabar, P., Peressutti, D., van der Stoep, J., Reymen, B., Emans, D., Hattu, D., van Loon, J., et al. (2018) · Medical Physics

Medical Image Segmentation TechniquesAdvanced Radiotherapy Techniques

Cited by 89

From cloud computing to sky computing

Stoica, I., & Shenker, S. (2021) · Proceedings of the Workshop on Hot Topics in Operating Systems

Cloud Computing and Resource ManagementSoftware-Defined Networks and 5G

Cited by 89

Datafied child welfare services: unpacking politics, economics and power

Redden, J., Dencik, L., & Warne, H. (2020) · Policy Studies

Ethics and Social Impacts of AIChild Welfare and Adoption

Cited by 89

The Machine Learning Machine: A Tangible User Interface for Teaching Machine Learning

Kaspersen, M. H., Bilstrup, K.-E. K., & Petersen, M. G. (2021) · Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction

Teaching and Learning ProgrammingInteractive and Immersive Displays

Cited by 89

Blockchain for Privacy Preserving and Trustworthy Distributed Machine Learning in Multicentric Medical Imaging (C-DistriM)

Zerka, F., Urovi, V., Vaidyanathan, A., Barakat, S., Leijenaar, R. T. H., Walsh, S., Gabrani-Juma, H., Miraglio, B., Woodruff, H. C., Dumontier, M., et al. (2020) · IEEE Access

Blockchain Technology Applications and SecurityPrivacy-Preserving Technologies in Data

Cited by 89

What Deserves Memory: Adaptive Memory Distillation for LLM Agents

Ma, W., Nan, J., & Wu, W. (2026) · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

AI-based Problem Solving and PlanningTopic Modeling

Cited by 89

Ten quick tips for teaching programming

Brown, N. C. C., & Wilson, G. (2018) · PLOS Computational Biology

Teaching and Learning ProgrammingInnovative Teaching Methods

Cited by 89

Human-artificial interaction in the age of agentic AI: a system-theoretical approach

Borghoff, U. M., Bottoni, P., & Pareschi, R. (2025) · Frontiers in Human Dynamics

Multi-Agent Systems and NegotiationInformation Systems Theories and Implementation

Cited by 89

Artificial Astrocytes Improve Neural Network Performance

Porto-Pazos, A. B., Veiguela, N., Mesejo, P., Navarrete, M., Alvarellos, A., Ibáñez, O., Pazos, A., & Araque, A. (2011) · PLoS ONE

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 89

Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework

Sathupadi, K., Achar, S., Bhaskaran, S. V., Faruqui, N., Abdullah-Al-Wadud, M., & Uddin, J. (2024) · Sensors

IoT and Edge/Fog ComputingReliability and Maintenance Optimization

Cited by 89

Decision trees do not generalize to new variations

Bengio, Y., Delalleau, O., & Simard, C. (2010) · Computational Intelligence

Data Mining Algorithms and ApplicationsMachine Learning and Algorithms

Cited by 89

Quod erat demonstrandum? - Towards a typology of the concept of explanation for the design of explainable AI

Cabitza, F., Campagner, A., Malgieri, G., Natali, C., Schneeberger, D., Stoeger, K., & Holzinger, A. (2023) · Expert Systems with Applications

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

Cited by 89

Abstract representations emerge naturally in neural networks trained to perform multiple tasks

Johnston, W. J., & Fusi, S. (2023) · Nature Communications

Domain Adaptation and Few-Shot LearningNeural Networks and Applications

Cited by 89