Check computer science papers: citations, claims and retractions

Learned Step Size Quantization

Esser, S. K., McKinstry, J. L., Bablani, D., Appuswamy, R., & Modha, D. S. (2019) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 415

Benchmarking Large Language Models for News Summarization

Zhang, T., Ladhak, F., Durmus, E., Liang, P., McKeown, K., & Hashimoto, T. B. (2024) · Transactions of the Association for Computational Linguistics

Topic ModelingAdvanced Text Analysis Techniques

Cited by 415

Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare

Goh, K. H., Wang, L., Yeow, A. Y. K., Poh, H., Li, K., Yeow, J. J. L., & Tan, G. Y. H. (2021) · Nature Communications

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 415

Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks

Santos, C. F. G. D., & Papa, J. P. (2022) · ACM Computing Surveys

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 415

Neural basis of embodiment: distinct contributions of temporoparietal junction and extrastriate body area

Arzy, S., Thut, G., Mohr, C., Michel, C. M., & Blanke, O. (2006) · The Journal of Neuroscience

Virtual Reality Applications and ImpactsTactile and Sensory Interactions

Cited by 415

Stim: a fast stabilizer circuit simulator

Gidney, C. (2021) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 415

Clipper: A Low-Latency Online Prediction Serving System

Crankshaw, D., Wang, X., Zhou, G., Franklin, M. J., Gonzalez, J. E., & Stoica, I. (2016) · arXiv

Cloud Computing and Resource ManagementData Stream Mining Techniques

Cited by 415

A Modified YOLOv8 Detection Network for UAV Aerial Image Recognition

Li, Y., Fan, Q., Huang, H., Han, Z., & Gu, Q. (2023) · Drones

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 415

Monocular‐SLAM–based navigation for autonomous micro helicopters in GPS‐denied environments

Weiss, S., Scaramuzza, D., & Siegwart, R. (2011) · Journal of Field Robotics

Robotics and Sensor-Based LocalizationAerospace Engineering and Control Systems

Cited by 414

Perceiver: General Perception with Iterative Attention

Jaegle, A., Gimeno, F., Brock, A., Zisserman, A., Vinyals, O., & Carreira, J. (2021) · arXiv

Advanced Neural Network ApplicationsMultimodal Machine Learning Applications

Cited by 414

MedMNIST Classification Decathlon: A Lightweight AutoML Benchmark for Medical Image Analysis

Yang, J., Shi, R., & Ni, B. (2021) · 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)

Machine Learning and Data ClassificationDomain Adaptation and Few-Shot Learning

Cited by 414

Internet of Things Intrusion Detection: Centralized, On-Device, or Federated Learning?

Rahman, S. A., Tout, H., Talhi, C., & Mourad, A. (2020) · IEEE Network

Network Security and Intrusion DetectionPrivacy-Preserving Technologies in Data

Cited by 414

Racial Bias in Hate Speech and Abusive Language Detection Datasets

Davidson, T., Bhattacharya, D., & Weber, I. (2019) · Proceedings of the Third Workshop on Abusive Language Online

Hate Speech and Cyberbullying DetectionEthics and Social Impacts of AI

Cited by 414

How to evaluate technologies for health behavior change in HCI research

Klasnja, P., Consolvo, S., & Pratt, W. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionMobile Health and mHealth Applications

Cited by 414

Neural Machine Translation in Linear Time

Kalchbrenner, N., Espeholt, L., Simonyan, K., Oord, A. V. D., Graves, A., & Kavukcuoglu, K. (2016) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 414

Automatic acoustic detection of birds through deep learning: The first Bird Audio Detection challenge

Stowell, D., Wood, M. D., Pamuła, H., Stylianou, Y., & Glotin, H. (2019) · Methods in Ecology and Evolution

Music and Audio ProcessingAnimal Vocal Communication and Behavior

Cited by 414

Emotion recognition in human–computer interaction

Fragopanagos, N., & Taylor, J. G. (2005) · Neural Networks

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 414

Rise of the expert amateur: DIY projects, communities, and cultures

Kuznetsov, S., & Paulos, E. (2010) · Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries

Open Source Software InnovationsInnovative Human-Technology Interaction

Cited by 413

Fine-Tuning Language Models from Human Preferences

Ziegler, D. M., Stiennon, N., Wu, J., Brown, T. B., Radford, A., Amodei, D., Christiano, P., & Irving, G. (2019) · arXiv

Topic ModelingReinforcement Learning in Robotics

Cited by 413

Mobile-edge computing architecture: the role of mec in the internet of things

Sabella, D., Vaillant, A., Kuure, P., Rauschenbach, U., & Giust, F. (2016) · IEEE Consumer Electronics Magazine

IoT and Edge/Fog ComputingAdvanced Data and IoT Technologies

Cited by 413

Self-supervised learning for recommender systems: A survey

Yu, J., Yin, H., Xia, X., Chen, T., Li, J., & Huang, Z. (2024) · IEEE Transactions on Knowledge and Data Engineering

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 413

How are Java software developers using the Eclipse IDE?

Murphy, G. C., Kersten, M., & Findlater, L. (2006) · IEEE Software

Software Engineering Techniques and PracticesSoftware Engineering Research

Cited by 413

Cooperative Inverse Reinforcement Learning

Hadfield-Menell, D., Dragan, A., Abbeel, P., & Russell, S. (2016) · arXiv

Reinforcement Learning in RoboticsMachine Learning and Algorithms

Cited by 413

Empath: Understanding Topic Signals in Large-Scale Text

Fast, E., Chen, B., & Bernstein, M. S. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

Sentiment Analysis and Opinion MiningComputational and Text Analysis Methods

Cited by 413