Check computer science papers: citations, claims and retractions

Dynamic ElecTronic hEalth reCord deTection (DETECT) of individuals at risk of a first episode of psychosis: a case-control development and validation study

Raket, L. L., Jaskolowski, J., Kinon, B. J., Brasen, J. C., Jönsson, L., Wehnert, A., & Fusar-Poli, P. (2020) · The Lancet Digital Health

Machine Learning in HealthcareSchizophrenia research and treatment

Cited by 60

Data-driven event triggering for IoT applications

Kolios, P., Panayiotou, C., Ellinas, G., & Polycarpou, M. (2016) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingIoT Networks and Protocols

Cited by 60

On the Monte carlo boolean decision tree complexity of read‐once formulae

Santha, M. (1995) · Random Structures & Algorithms

Complexity and Algorithms in GraphsAdvanced Graph Theory Research

Cited by 60

Central Server Free Federated Learning over Single-sided Trust Social Networks

He, C., Tan, C., Tang, H., Qiu, S., & Liu, J. (2019) · arXiv

Privacy-Preserving Technologies in DataDistributed Control Multi-Agent Systems

Cited by 60

Cyberbullying Detection: An Overview

Hamiza Wan Ali, W. N., Mohd, M., & Fauzi, F. (2018) · 2018 Cyber Resilience Conference (CRC)

Hate Speech and Cyberbullying DetectionSpam and Phishing Detection

Cited by 60

Interpretability of Machine Learning Solutions in Public Healthcare: The CRISP-ML Approach

Kolyshkina, I., & Simoff, S. (2021) · Frontiers in Big Data

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare

Cited by 60

Rover-IRL: Inverse Reinforcement Learning With Soft Value Iteration Networks for Planetary Rover Path Planning

Pflueger, M., Agha, A., & Sukhatme, G. S. (2019) · IEEE Robotics and Automation Letters

Reinforcement Learning in RoboticsRobotic Path Planning Algorithms

Cited by 60

Revisiting Parameter-Efficient Tuning: Are We Really There Yet?

Chen, G., Liu, F., Meng, Z., & Liang, S. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 60

OpenPrompt: An Open-source Framework for Prompt-learning

Ding, N., Hu, S., Zhao, W., Chen, Y., Liu, Z., Zheng, H.-T., & Sun, M. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 60

An efficient security risk estimation technique for Risk-based access control model for IoT

Atlam, H. F., & Wills, G. B. (2019) · Internet of Things

Access Control and TrustInformation and Cyber Security

Cited by 60

Foundation Models for Decision Making: Problems, Methods, and Opportunities

Yang, S., Nachum, O., Du, Y., Wei, J., Abbeel, P., & Schuurmans, D. (2023) · arXiv

Multimodal Machine Learning ApplicationsAI-based Problem Solving and Planning

Cited by 60

EW-Tune: A Framework for Privately Fine-Tuning Large Language Models with Differential Privacy

Behnia, R., Ebrahimi, M. R., Pacheco, J., & Padmanabhan, B. (2022) · 2022 IEEE International Conference on Data Mining Workshops (ICDMW)

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 60

Monitoring the impact of stress on the sleep patterns of pilgrims using wearable sensors

Muaremi, A., Bexheti, A., Gravenhorst, F., Arnrich, B., & Troster, G. (2014) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

Emotion and Mood RecognitionContext-Aware Activity Recognition Systems

Cited by 60

Rethinking AI for good governance

Margetts, H. (2022) · Daedalus

Ethics and Social Impacts of AIE-Government and Public Services

Cited by 60

Uncovering Trajectories of Informal Learning in Large Online Communities of Creators

Yang, S., Domeniconi, C., Revelle, M., Sweeney, M., Gelman, B. U., Beckley, C., & Johri, A. (2015) · Proceedings of the Second (2015) ACM Conference on Learning @ Scale

Teaching and Learning ProgrammingOnline Learning and Analytics

Cited by 60

A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model

Xu, Y., Wang, Y., Zhou, F., Ma, J., Jin, C., Yang, S., Li, J., Zhang, Z., Zhao, C., Zhou, H., et al. (2024) · arXiv

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 60

An exploratory study of eye typing fundamentals: dwell time, text entry rate, errors, and workload

Räihä, K.-J., & Ovaska, S. (2012) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Gaze Tracking and Assistive TechnologyUsability and User Interface Design

Cited by 60

Empathic design: Research strategies

Thomas, J. (2013) · Australasian Medical Journal

Innovative Human-Technology InteractionDesign Education and Practice

Cited by 60

Efficient multi-prompt evaluation of LLMs

Polo, F., Xu, R., Weber, L., Silva, M., Bhardwaj, O., Choshen, L., Oliveira, A. D., Sun, Y., & Yurochkin, M. (2024) · Advances in Neural Information Processing Systems 37

Topic ModelingNatural Language Processing Techniques

Cited by 60

Using human knowledge awareness to adapt collaborative plan generation, explanation and monitoring

Milliez, G., Lallement, R., Fiore, M., & Alami, R. (2016) · 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

AI-based Problem Solving and PlanningSocial Robot Interaction and HRI

Cited by 60

ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Men, X., Xu, M., Zhang, Q., Wang, B., Lin, H., Lu, Y., Han, X., & Chen, W. (2024) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 60

Design Recommendations for Self-Monitoring in the Workplace: Studies in Software Development

Meyer, A. N., Murphy, G. C., Zimmermann, T., & Fritz, T. (2017) · Proceedings of the ACM on Human-Computer Interaction

Innovative Human-Technology InteractionPersonal Information Management and User Behavior

Cited by 60

Cryptanalysis and improvement of the hyper-chaotic image encryption scheme based on DNA encoding and scrambling

Feng, W., & He, Y.-G. (2018) · IEEE Photonics Journal

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 60

Round or square? How screen shape affects utilitarian and hedonic motivations for smartwatch adoption

Kim, K. J. (2016) · Cyberpsychology, Behavior, and Social Networking

Innovative Human-Technology InteractionTechnology Adoption and User Behaviour

Cited by 60