Check computer science papers: citations, claims and retractions

t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification

Kinnunen, T., Lee, K. A., Delgado, H., Evans, N., Todisco, M., Sahidullah, M., Yamagishi, J., & Reynolds, D. A. (2018) · The Speaker and Language Recognition Workshop (Odyssey 2018)

Speech Recognition and SynthesisBiometric Identification and Security

Cited by 198

Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning

Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., Rakovic, M., Molenaar, I., Moore, J., & Gašević, D. (2023) · Computers in Human Behavior

Intelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning Methods

Cited by 198

A Scholarly Definition of Artificial Intelligence (AI): Advancing AI as a Conceptual Framework in Communication Research

Gil de Zúñiga, H., Goyanes, M., & Durotoye, T. (2024) · Political Communication

Artificial Intelligence ApplicationsEthics and Social Impacts of AI

Cited by 198

Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review.

Block, V. A. J., Pitsch, E., Tahir, P., Cree, B. A. C., Allen, D. D., & Gelfand, J. M. (2016) · PLOS ONE

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 198

Latent bias and the implementation of artificial intelligence in medicine

DeCamp, M., & Lindvall, C. (2020) · Journal of the American Medical Informatics Association

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 198

Digital deception: generative artificial intelligence in social engineering and phishing

Schmitt, M., & Flechais, I. (2024) · Artificial Intelligence Review

Spam and Phishing DetectionAdversarial Robustness in Machine Learning

Cited by 198

Deep Learning Models for Classification of Red Blood Cells in Microscopy Images to Aid in Sickle Cell Anemia Diagnosis

Alzubaidi, L., Fadhel, M. A., Al-Shamma, O., Zhang, J., & Duan, Y. (2020) · Electronics

Digital Imaging for Blood DiseasesCell Image Analysis Techniques

Cited by 197

OC-FakeDect: Classifying Deepfakes Using One-class Variational Autoencoder

Khalid, H., & Woo, S. S. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Digital Media Forensic DetectionFace recognition and analysis

Cited by 197

Quantum simulations of materials on near-term quantum computers

Ma, H., Govoni, M., & Galli, G. (2020) · npj Computational Materials

Quantum Computing Algorithms and ArchitectureAdvanced Chemical Physics Studies

Cited by 197

Continuous Convolutional Neural Network with 3D Input for EEG-Based Emotion Recognition

Yang, Y., Wu, Q., Fu, Y., & Chen, X. (2018) · Lecture Notes in Computer Science

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 197

Modern computing: Vision and challenges

Gill, S. S., Wu, H., Patros, P., Ottaviani, C., Arora, P., Pujol, V. C., Haunschild, D., Parlikad, A. K., Cetinkaya, O., Lutfiyya, H., et al. (2024) · Telematics and Informatics Reports

History of Computing TechnologiesCloud Computing and Resource Management

Cited by 197

Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics

Pagnoni, A., Balachandran, V., & Tsvetkov, Y. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingAdvanced Text Analysis Techniques

Cited by 197

Artificial Intelligence and Sustainable Decisions

Zhao, J., & Gómez Fariñas, B. (2023) · European Business Organization Law Review

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 197

Serf and turf: crowdturfing for fun and profit

Wang, G., Wilson, C., Zhao, X., Zhu, Y., Mohanlal, M., Zheng, H., & Zhao, B. Y. (2012) · Proceedings of the 21st international conference on World Wide Web

Spam and Phishing DetectionMobile Crowdsensing and Crowdsourcing

Cited by 197

Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models

Wu, C., Yin, S., Qi, W., Wang, X., Tang, Z., & Duan, N. (2023) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 197

Universal and Transferable Adversarial Attacks on Aligned Language Models

Zou, A., Wang, Z., Carlini, N., Nasr, M., Kolter, J. Z., & Fredrikson, M. (2023) · arXiv

Adversarial Robustness in Machine LearningSpeech Recognition and Synthesis

Cited by 197

GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Frantar, E., Ashkboos, S., Hoefler, T., & Alistarh, D. (2022) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 197

Virtual reality for supporting the treatment of depression and anxiety: scoping review

Baghaei, N., Chitale, V., Hlasnik, A., Stemmet, L., Liang, H.-N., & Porter, R. (2021) · JMIR Mental Health

Virtual Reality Applications and ImpactsDigital Mental Health Interventions

Cited by 197

ScanQA: 3D Question Answering for Spatial Scene Understanding

Azuma, D., Miyanishi, T., Kurita, S., & Kawanabe, M. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning Applications3D Shape Modeling and Analysis

Cited by 197

What Makes Multi-modal Learning Better than Single (Provably)

Huang, Y., Du, C., Xue, Z., Chen, X., Zhao, H., & Huang, L. (2021) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 197

Artificial Intelligence Policy: A Primer and Roadmap

Calo, R. (2018) · University of Bologna Law Review

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 197

End-to-end spectro-temporal graph attention networks for speaker verification anti-spoofing and speech deepfake detection

Tak, H., Jung, J.-W., Patino, J., Kamble, M., Todisco, M., & Evans, N. (2021) · 2021 Edition of the Automatic Speaker Verification and Spoofing Countermeasures Challenge

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 197

Towards a Science of Scaling Agent Systems

Kim, Y., Gu, K., Park, C., Park, C., Schmidgall, S., Heydari, A. A., Yan, Y., Zhang, Z., Zhuang, Y., Liu, Y., et al. (2025) · arXiv

Multi-Agent Systems and NegotiationAI-based Problem Solving and Planning

Cited by 197

Rrpn: Radar region proposal network for object detection in autonomous vehicles

Nabati, R., & Qi, H. (2019) · 2019 IEEE International Conference on Image Processing (ICIP)

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 197