Most cited computer science papers
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Human stress classification during public speaking using physiological signals
Arsalan, A., & Majid, M. (2021) · Computers in Biology and Medicine
Emotion and Mood RecognitionHeart Rate Variability and Autonomic Control
Cited by 77
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Gymnasium
Towers, M., Terry, J. K., Kwiatkowski, A., Balis, J. U., Cola, G., Deleu, T., Goulão, M., Kallinteris, A., KG, A., Krimmel, M., et al. (2024) · Zenodo
Reinforcement Learning in RoboticsArtificial Intelligence in Games
Cited by 77
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Does your dermatology classifier know what it doesn’t know? Detecting the long-tail of unseen conditions
Guha Roy, A., Ren, J., Azizi, S., Loh, A., Natarajan, V., Mustafa, B., Pawlowski, N., Freyberg, J., Liu, Y., Beaver, Z., et al. (2022) · Medical Image Analysis
Anomaly Detection Techniques and ApplicationsCutaneous Melanoma Detection and Management
Cited by 77
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FPGA-Accelerated Dense Linear Machine Learning: A Precision-Convergence Trade-Off
Kara, K., Alistarh, D., Alonso, G., Mutlu, O., & Zhang, C. (2017) · 2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)
Embedded Systems Design TechniquesNumerical Methods and Algorithms
Cited by 77
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Movement model, hits distribution and learning in virtual keyboarding
Zhai, S., Sue, A., & Accot, J. (2002) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Interactive and Immersive DisplaysUsability and User Interface Design
Cited by 77
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Will Pyramids Built of Nuggets Topple Over?
Lin, J., & Demner-Fushman, D. (2006) · Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics -
Information Retrieval and Search BehaviorTopic Modeling
Cited by 77
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Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery
Wen, Y., Jain, N., Kirchenbauer, J., Goldblum, M., Geiping, J., & Goldstein, T. (2023) · arXiv
Topic ModelingDomain Adaptation and Few-Shot Learning
Cited by 77
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Survey: Leakage and Privacy at Inference Time
Jegorova, M., Kaul, C., Mayor, C., O'Neil, A. Q., Weir, A., Murray-Smith, R., & Tsaftaris, S. A. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence
Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning
Cited by 77
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AI safety on whose terms?
Lazar, S., & Nelson, A. (2023) · Science
Ethics and Social Impacts of AISafety Systems Engineering in Autonomy
Cited by 77
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Object Detection for Autonomous Driving using YOLO [You Only Look Once] algorithm
Sarda, A., Dixit, S., & Bhan, A. (2021) · 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV)
Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety
Cited by 77
- Verified · note
Cultural Bias in Large Language Models: A Comprehensive Analysis and Mitigation Strategies
Liu, Z. (2025) · Journal of Transcultural Communication
Ethics and Social Impacts of AITopic Modeling
Cited by 77
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Photonic Matrix Computing: From Fundamentals to Applications
Cheng, J., Zhou, H., & Dong, J. (2021) · Nanomaterials
Neural Networks and Reservoir ComputingPhotonic and Optical Devices
Cited by 76
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Designing an Interpretability-Based Model to Explain the Artificial Intelligence Algorithms in Healthcare
Ennab, M., & Mcheick, H. (2022) · Diagnostics
Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education
Cited by 76
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AI-Powered Blockchain - A Decentralized Secure Multiparty Computation Protocol for IoV
Raja, G., Manaswini, Y., Vivekanandan, G. D., Sampath, H., Dev, K., & Bashir, A. K. (2020) · IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
Blockchain Technology Applications and SecurityVehicular Ad Hoc Networks (VANETs)
Cited by 76
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In ChatGPT We Trust? Measuring and Characterizing the Reliability of ChatGPT
Shen, X., Chen, Z., Backes, M., & Zhang, Y. (2023) · arXiv
Adversarial Robustness in Machine LearningTopic Modeling
Cited by 76
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The effect of immersion on sense of presence and affect when experiencing an educational scenario in virtual reality: A randomized controlled study
Lønne, T. F., Karlsen, H. R., Langvik, E., & Saksvik-Lehouillier, I. (2023) · Heliyon
Virtual Reality Applications and ImpactsFlow Experience in Various Fields
Cited by 76
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Informing Age-Appropriate AI: Examining Principles and Practices of AI for Children
Wang, G., Zhao, J., Van Kleek, M., & Shadbolt, N. (2022) · CHI Conference on Human Factors in Computing Systems
Ethics and Social Impacts of AIChild Development and Digital Technology
Cited by 76
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State of the Art of Machine Learning–Enabled Clinical Decision Support in Intensive Care Units: Literature Review
Hong, N., Liu, C., Gao, J., Han, L., Chang, F., Gong, M., & Su, L. (2022) · JMIR Medical Informatics
Machine Learning in HealthcareArtificial Intelligence in Healthcare
Cited by 76
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Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
Cai, Z. (2021) · npj Quantum Information
Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography
Cited by 76
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Secure and Trusted Execution: Past, Present, and Future - A Critical Review in the Context of the Internet of Things and Cyber-Physical Systems
Shepherd, C., Arfaoui, G., Gurulian, I., Lee, R. P., Markantonakis, K., Akram, R. N., Sauveron, D., & Conchon, E. (2016) · 2016 IEEE Trustcom/BigDataSE/ISPA
Security and Verification in ComputingDigital Rights Management and Security
Cited by 76
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XAI Evaluation: Evaluating Black-Box Model Explanations for Prediction
Zhang, Y., Xu, F., Zou, J., Petrosian, O. L., & Krinkin, K. V. (2021) · 2021 II International Conference on Neural Networks and Neurotechnologies (NeuroNT)
Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques
Cited by 76
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Resurrecting Recurrent Neural Networks for Long Sequences
Orvieto, A., Smith, S. L., Gu, A., Fernando, A., Gulcehre, C., Pascanu, R., & De, S. (2023) · arXiv
Neural Networks and ApplicationsTopic Modeling
Cited by 76
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Free-riders in Federated Learning: Attacks and Defenses
Lin, J., Du, M., & Liu, J. (2019) · arXiv
Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning
Cited by 76
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Understanding Emergent Abilities of Language Models from the Loss Perspective
Du, Z., Zeng, A., Dong, Y., & Tang, J. (2024) · Advances in Neural Information Processing Systems 37
Topic ModelingNatural Language Processing Techniques
Cited by 76
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