Check computer science papers: citations, claims and retractions

Reflective design

Sengers, P., Boehner, K., David, S., & Kaye, J. '. (2005) · Proceedings of the 4th decennial conference on Critical computing: between sense and sensibility

Innovative Human-Technology InteractionEthics and Social Impacts of AI

Cited by 1,030

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

Mehta, S., Rastegari, M., Caspi, A., Shapiro, L., & Hajishirzi, H. (2018) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,029

Large Language Models for Software Engineering: A Systematic Literature Review

Hou, X., Zhao, Y., Liu, Y., Yang, Z., Wang, K., Li, L., Luo, X., Lo, D., Grundy, J., & Wang, H. (2024) · ACM Transactions on Software Engineering and Methodology

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 1,029

A Hybrid Approach to Privacy-Preserving Federated Learning

Truex, S., Baracaldo, N., Anwar, A., Steinke, T., Ludwig, H., Zhang, R., & Zhou, Y. (2019) · Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 1,029

RETAIN: an interpretable predictive model for healthcare using reverse time attention mechanism

Choi, E., Bahadori, M. T., Kulas, J. A., Schuetz, A., Stewart, W. F., & Sun, J. (2016) · arXiv

Machine Learning in HealthcareExplainable Artificial Intelligence (XAI)

Cited by 1,029

MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling

Budzianowski, P., Wen, T.-H., Tseng, B.-H., Casanueva, I., Ultes, S., Ramadan, O., & Gašić, M. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Speech and dialogue systemsAI in Service Interactions

Cited by 1,028

An MTurk Crisis? Shifts in Data Quality and the Impact on Study Results

Chmielewski, M., & Kucker, S. C. (2020) · Social Psychological and Personality Science

Mobile Crowdsensing and CrowdsourcingSurvey Methodology and Nonresponse

Cited by 1,027

A deep learning framework for neuroscience

Richards, B. A., Lillicrap, T. P., Beaudoin, P., Bengio, Y., Bogacz, R., Christensen, A., Clopath, C., Costa, R. P., de Berker, A., Ganguli, S., et al. (2019) · Nature Neuroscience

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 1,027

A Review of Data Fusion Techniques

Castanedo, F. (2013) · The Scientific World Journal

Target Tracking and Data Fusion in Sensor NetworksInertial Sensor and Navigation

Cited by 1,027

Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images

Saltz, J., Gupta, R., Hou, L., Kurc, T., Singh, P., Nguyen, V., Samaras, D., Shroyer, K. R., Zhao, T., Batiste, R., et al. (2018) · Cell Reports

AI in cancer detectionCancer Immunotherapy and Biomarkers

Cited by 1,027

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Salimans, T., Ho, J., Chen, X., Sidor, S., & Sutskever, I. (2017) · arXiv

Reinforcement Learning in RoboticsEvolutionary Algorithms and Applications

Cited by 1,027

A note on the evaluation of generative models

Theis, L., Oord, A. V. D., & Bethge, M. (2015) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 1,026

Understanding the Motivations, Participation, and Performance of Open Source Software Developers: A Longitudinal Study of the Apache Projects

Roberts, J. A., Hann, I.-H., & Slaughter, S. A. (2006) · Management Science

Open Source Software InnovationsSoftware Engineering Techniques and Practices

Cited by 1,024

Automated model-based tissue classification of MR images of the brain

Van Leemput, K., Maes, F., Vandermeulen, D., & Suetens, P. (1999) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,024

HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation

Cheng, B., Xiao, B., Wang, J., Shi, H., Huang, T. S., & Zhang, L. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Human Pose and Action RecognitionAdvanced Neural Network Applications

Cited by 1,023

Quantum mechanical computers

Feynman, R. P. (1985) · Optics News

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,023

LAION-5B: An open large-scale dataset for training next generation image-text models

Schuhmann, C., Beaumont, R., Vencu, R., Gordon, C., Wightman, R., Cherti, M., Coombes, T., Katta, A., Mullis, C., Wortsman, M., et al. (2022) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 1,022

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R. H., Morrow, M. J., & Polakos, P. A. (2018) · IEEE Communications Surveys & Tutorials

IoT and Edge/Fog ComputingCloud Computing and Resource Management

Cited by 1,022

Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates

Kudo, T. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 1,021

A hierarchical model for object-oriented design quality assessment

Bansiya, J., & Davis, C. G. (2002) · IEEE Transactions on Software Engineering

Software Engineering ResearchAdvanced Software Engineering Methodologies

Cited by 1,020

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing

Kumar, A., Irsoy, O., Ondruska, P., Iyyer, M., Bradbury, J., Gulrajani, I., Zhong, V., Paulus, R., & Socher, R. (2015) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,020

Monocular 3D Object Detection for Autonomous Driving

Chen, X., Kundu, K., Zhang, Z., Ma, H., Fidler, S., & Urtasun, R. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 1,019

Multi-attentional Deepfake Detection

Zhao, H., Wei, T., Zhou, W., Zhang, W., Chen, D., & Yu, N. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 1,019

Randomized benchmarking of quantum gates

Knill, E., Leibfried, D., Reichle, R., Britton, J., Blakestad, R. B., Jost, J. D., Langer, C., Ozeri, R., Seidelin, S., & Wineland, D. J. (2008) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,019