Check computer science papers: citations, claims and retractions

HM-CONFORMER: A Conformer-Based Audio Deepfake Detection System with Hierarchical Pooling and Multi-Level Classification Token Aggregation Methods

Shin, H.-S., Heo, J., Kim, J.-H., Lim, C.-Y., Kim, W., & Yu, H.-J. (2024) · ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 21

Efficient LLM Scheduling by Learning to Rank

Fu, Y., Zhu, S., Su, R., Qiao, A., Stoica, I., & Zhang, H. (2024) · arXiv

Cloud Computing and Resource ManagementDistributed and Parallel Computing Systems

Cited by 21

Toward Bulk Synchronous Parallel-Based Machine Learning Techniques for Anomaly Detection in High-Speed Big Data Networks

Siddique, K., Akhtar, Z., Lee, H.-G., Kim, W., & Kim, Y. (2017) · Symmetry

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 21

Objective ventricle segmentation in brain CT with ischemic stroke based on anatomical knowledge

Qian, X., Lin, Y., Zhao, Y., Yue, X., Lu, B., & Wang, J. (2017) · BioMed Research International

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 21

The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Marks, S., & Tegmark, M. (2023) · arXiv

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 21

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images

van Eekelen, L., Spronck, J., Looijen-Salamon, M., Vos, S., Munari, E., Girolami, I., Eccher, A., Acs, B., Boyaci, C., de Souza, G. S., et al. (2024) · Scientific Reports

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 21

Research Products at Scale: Learnings from Designing Devices in Multiples of Ones, Tens, Hundreds and Thousands

Boucher, A. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionDesign Education and Practice

Cited by 21

Efficient LLMs for Edge Devices: Pruning, Quantization, and Distillation Techniques

Agrawal, R., Kumar, H., & Lnu, S. R. (2025) · 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS)

Advanced Neural Network ApplicationsTopic Modeling

Cited by 21

Identification of Deadliest Mosquitoes Using Wing Beats Sound Classification on Tiny Embedded System Using Machine Learning and Edge Impulse Platform

Trivedi, K., & Shroff, H. (2021) · 2021 ITU Kaleidoscope: Connecting Physical and Virtual Worlds (ITU K)

Music and Audio ProcessingArduino and IoT Applications

Cited by 21

Multi-Level Over-the-Air Aggregation of Mobile Edge Computing Over D2D Wireless Networks

Wang, F., & Lau, V. K. N. (2022) · IEEE Transactions on Wireless Communications

IoT and Edge/Fog ComputingAdvanced MIMO Systems Optimization

Cited by 21

Practitioners’ expectations on log anomaly detection

Ma, X., Li, Y., Keung, J., Yu, X., Zou, H., Yang, Z., Sarro, F., & Barr, E. T. (2025) · IEEE Transactions on Software Engineering

Software System Performance and ReliabilitySoftware Engineering Techniques and Practices

Cited by 21

A web-based model to enhance algorithmic thinking for novice programmers

Iqbal Malik, S., Mathew, R., Tawafak, R. M., & Alfarsi, G. (2021) · E-Learning and Digital Media

Teaching and Learning ProgrammingProblem and Project Based Learning

Cited by 21

Navigating the DevOps landscape

Zhang, X., Zhao, P., & Jaskolka, J. (2025) · Journal of Systems and Software

Software Engineering Techniques and PracticesSoftware System Performance and Reliability

Cited by 21

A comprehensive survey on energy-efficient and privacy-preserving federated learning for edge intelligence and IoT

Alahmari, S., & Alghamdi, I. (2025) · Results in Engineering

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 21

Introduction to Scientific Data Mining: Direct Kernel Methods and Applications

Embrechts, M. J., Szymanski, B., & Sternickel, K. (2004) · Computationally Intelligent Hybrid Systems

Machine Learning and ELMData Mining and Machine Learning Applications

Cited by 21

Monitoring file integrity using blockchain and smart contracts

Pinheiro, A., Canedo, E. D., De Sousa, R. T., & De Oliveira Albuquerque, R. (2020) · IEEE Access

Blockchain Technology Applications and SecurityCloud Data Security Solutions

Cited by 21

The temporal dynamics of visual attention.

Zhang, H., Sellers, J., Lee, T. G., & Jonides, J. (2025) · Journal of Experimental Psychology: General

Visual Attention and Saliency DetectionVisual perception and processing mechanisms

Cited by 21

The “Ethics” of Teaching Ethical Hacking

Pike, R. E. (2013) · Journal of International Technology and Information Management

Information and Cyber SecurityInformation Systems Education and Curriculum Development

Cited by 21

Multimodal Emotion Recognition: Emotion Classification Through the Integration of EEG and Facial Expressions

Erdem Güler, S., & Patlar Akbulut, F. (2025) · IEEE Access

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 21

Scaling and evaluating sparse autoencoders

Gao, L., la Tour, T. D., Tillman, H., Goh, G., Troll, R., Radford, A., Sutskever, I., Leike, J., & Wu, J. (2024) · arXiv

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 21

Natural language processing for adjudication of heart failure in the electronic health record

Cunningham, J. W., Singh, P., Reeder, C., Lau, E. S., Khurshid, S., Wang, X., Ellinor, P. T., Lubitz, S. A., Batra, P., & Ho, J. E. (2023) · JACC: Heart Failure

Machine Learning in HealthcareHeart Failure Treatment and Management

Cited by 21

Siamese Networks for Weakly Supervised Human Activity Recognition

Sheng, T., & Huber, M. (2019) · 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)

Context-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Cited by 21

Detecting sexual predators in chats using behavioral features and imbalanced learning

CARDEI, C., & REBEDEA, T. (2017) · Natural Language Engineering

Hate Speech and Cyberbullying DetectionText and Document Classification Technologies

Cited by 21

Quantized recurrence time in unital iterated open quantum dynamics

Sinkovicz, P., Kurucz, Z., Kiss, T., & Asbóth, J. K. (2015) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications

Cited by 21