Check computer science papers: citations, claims and retractions

Cursor measures for motion-impaired computer users

Keates, S., Hwang, F., Langdon, P., Clarkson, P. J., & Robinson, P. (2002) · Proceedings of the fifth international ACM conference on Assistive technologies

Gaze Tracking and Assistive TechnologyAssistive Technology in Communication and Mobility

Cited by 84

Blockchain-orchestrated machine learning for privacy preserving federated learning in electronic health data

Passerat-Palmbach, J., Farnan, T., McCoy, M., Harris, J. D., Manion, S. T., Flannery, H. L., & Gleim, B. (2020) · 2020 IEEE International Conference on Blockchain (Blockchain)

Blockchain Technology Applications and SecurityPrivacy-Preserving Technologies in Data

Cited by 84

Selecting third-party libraries: the practitioners’ perspective

Larios Vargas, E., Aniche, M., Treude, C., Bruntink, M., & Gousios, G. (2020) · Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Software Engineering Techniques and PracticesSoftware Engineering Research

Cited by 84

Learning analytics to support teachers during synchronous CSCL: balancing between overview and overload

Van Leeuwen, A. (2015) · Journal of Learning Analytics

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 84

DualNet: Continual Learning, Fast and Slow

Pham, Q., Liu, C., & Hoi, S. (2021) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 84

DeepCham: Collaborative Edge-Mediated Adaptive Deep Learning for Mobile Object Recognition

Li, D., Salonidis, T., Desai, N. V., & Chuah, M. C. (2016) · 2016 IEEE/ACM Symposium on Edge Computing (SEC)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 84

Neural responses to heartbeats distinguish self from other during imagination

Babo-Rebelo, M., Buot, A., & Tallon-Baudry, C. (2019) · NeuroImage

Virtual Reality Applications and ImpactsPhilosophy and Theoretical Science

Cited by 84

Multimodal Emotion Recognition Using a Hierarchical Fusion Convolutional Neural Network

Zhang, Y., Cheng, C., & Zhang, Y. (2021) · IEEE Access

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 84

Markov equivalence for ancestral graphs

Ali, R. A., Richardson, T. S., & Spirtes, P. (2009) · The Annals of Statistics

Bayesian Modeling and Causal InferenceStatistical Methods and Inference

Cited by 84

Ransomware: To pay or not to pay?

Everett, C. (2016) · Computer Fraud & Security

Advanced Malware Detection TechniquesInformation and Cyber Security

Cited by 84

Revolution or evolution? Speech interaction and HCI design guidelines

Murad, C., Munteanu, C., Cowan, B. R., & Clark, L. (2019) · IEEE Pervasive Computing

Usability and User Interface DesignSpeech and dialogue systems

Cited by 84

The simulator sickness questionnaire, and the erroneous zero baseline assumption

Brown, P., Spronck, P., & Powell, W. (2022) · Frontiers in Virtual Reality

Virtual Reality Applications and ImpactsAdvanced Optical Imaging Technologies

Cited by 84

BERTese: Learning to Speak to BERT

Haviv, A., Berant, J., & Globerson, A. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Topic ModelingInformation Retrieval and Search Behavior

Cited by 84

GoalKeeper: Exploring Interaction Lockout Mechanisms for Regulating Smartphone Use

Kim, J., Jung, H., Ko, M., & Lee, U. (2019) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Innovative Human-Technology InteractionMobile Health and mHealth Applications

Cited by 84

Are We All in the Same "Bloat"?

McGrenere, J., & Moore, G. (2000) · Canadian Human-Computer Communications Society

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 84

Acoustic correlates of task load and stress

Scherer, K. R., Grandjean, D., Johnstone, T., Klasmeyer, G., & Bänziger, T. (2002) · 7th International Conference on Spoken Language Processing (ICSLP 2002)

Emotion and Mood RecognitionPhonetics and Phonology Research

Cited by 84

Understanding Circumstances for Desirable Proactive Behaviour of Voice Assistants: The Proactivity Dilemma

Zargham, N., Reicherts, L., Bonfert, M., Voelkel, S. T., Schoening, J., Malaka, R., & Rogers, Y. (2022) · Proceedings of the 4th Conference on Conversational User Interfaces

Innovative Human-Technology InteractionAI in Service Interactions

Cited by 84

The value of artificial intelligence in the diagnosis of lung cancer: A systematic review and meta-analysis

Liu, M., Wu, J., Wang, N., Zhang, X., Bai, Y., Guo, J., Zhang, L., Liu, S., & Tao, K. (2023) · PLOS ONE

AI in cancer detectionLung Cancer Diagnosis and Treatment

Cited by 84

Implicit Representations of Meaning in Neural Language Models

Li, B. Z., Nye, M., & Andreas, J. (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)

Topic ModelingNatural Language Processing Techniques

Cited by 84

A Systematic Review of Data Quality in CPS and IoT for Industry 4.0

Goknil, A., Nguyen, P., Sen, S., Politaki, D., Niavis, H., Pedersen, K. J., Suyuthi, A., Anand, A., & Ziegenbein, A. (2023) · ACM Computing Surveys

Data Quality and ManagementDigital Transformation in Industry

Cited by 84

Human-Centric Justification of Machine Learning Predictions

Biran, O., & McKeown, K. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

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

Cited by 84

Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference

Roeder, G., Wu, Y., & Duvenaud, D. (2017) · arXiv

Gaussian Processes and Bayesian InferenceMarkov Chains and Monte Carlo Methods

Cited by 84

Neural reverse engineering of stripped binaries using augmented control flow graphs

David, Y., Alon, U., & Yahav, E. (2020) · Proceedings of the ACM on Programming Languages

Software Engineering ResearchSecurity and Verification in Computing

Cited by 84

Root-Cause Metric Location for Microservice Systems via Log Anomaly Detection

Wang, L., Zhao, N., Chen, J., Li, P., Zhang, W., & Sui, K. (2020) · 2020 IEEE International Conference on Web Services (ICWS)

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 84