Check computer science papers: citations, claims and retractions

AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis

Guo, Y., Chen, K., Liang, S., Liu, Y.-J., Bao, H., & Zhang, J. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image Synthesis3D Shape Modeling and Analysis

Cited by 384

The ethics of algorithms: key problems and solutions

Tsamados, A., Aggarwal, N., Cowls, J., Morley, J., Roberts, H., Taddeo, M., & Floridi, L. (2022) · AI & SOCIETY

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 384

Smartphone-Based Recognition of States and State Changes in Bipolar Disorder Patients

Grunerbl, A., Muaremi, A., Osmani, V., Bahle, G., Ohler, S., Troster, G., Mayora, O., Haring, C., & Lukowicz, P. (2015) · IEEE Journal of Biomedical and Health Informatics

Context-Aware Activity Recognition SystemsEmotion and Mood Recognition

Cited by 384

The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing

Dror, R., Baumer, G., Shlomov, S., & Reichart, R. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 384

The geography of coordination: dealing with distance in R&D work

Grinter, R. E., Herbsleb, J. D., & Perry, D. E. (1999) · Proceedings of the international ACM SIGGROUP conference on Supporting group work

Software Engineering Techniques and PracticesProduct Development and Customization

Cited by 384

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning

Zhou, L.-Q., Wu, X.-L., Huang, S.-Y., Wu, G.-G., Ye, H.-R., Wei, Q., Bao, L.-Y., Deng, Y.-B., Li, X.-R., Cui, X.-W., et al. (2020) · Radiology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 384

Low-Dimensional Hyperbolic Knowledge Graph Embeddings

Chami, I., Wolf, A., Juan, D.-C., Sala, F., Ravi, S., & Ré, C. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Advanced Graph Neural NetworksTopic Modeling

Cited by 384

Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems

Kiritchenko, S., & Mohammad, S. (2018) · Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics

Ethics and Social Impacts of AISentiment Analysis and Opinion Mining

Cited by 384

Opinion Mining with Deep Recurrent Neural Networks

Irsoy, O., & Cardie, C. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 384

Learning high-dimensional directed acyclic graphs with latent and selection variables

Colombo, D., Maathuis, M. H., Kalisch, M., & Richardson, T. S. (2012) · The Annals of Statistics

Bayesian Modeling and Causal InferenceStatistical Methods and Inference

Cited by 384

Cultural bias and cultural alignment of large language models

Tao, Y., Viberg, O., Baker, R. S., & Kizilcec, R. F. (2024) · PNAS Nexus

Ethics and Social Impacts of AITopic Modeling

Cited by 383

Learning Self-Consistency for Deepfake Detection

Zhao, T., Xu, X., Xu, M., Ding, H., Xiong, Y., & Xia, W. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 383

Decentralized autonomous organization

Hassan, S., & De Filippi, P. (2021) · Internet Policy Review

Blockchain Technology Applications and SecurityDigital Transformation in Law

Cited by 383

Encoding Electronic Spectra in Quantum Circuits with Linear T Complexity

Babbush, R., Gidney, C., Berry, D. W., Wiebe, N., McClean, J., Paler, A., Fowler, A., & Neven, H. (2018) · Physical Review X

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 383

Learn To Pay Attention

Jetley, S., Lord, N. A., Lee, N., & Torr, P. H. S. (2018) · arXiv

Visual Attention and Saliency DetectionAdvanced Neural Network Applications

Cited by 383

Requirements for photoware

Frohlich, D., Kuchinsky, A., Pering, C., Don, A., & Ariss, S. (2002) · Proceedings of the 2002 ACM conference on Computer supported cooperative work

Innovative Human-Technology InteractionPersonal Information Management and User Behavior

Cited by 383

SUTime: A library for recognizing and normalizing time expressions

Chang, A. X., & Manning, C. (2012) · Proceedings of the Language Resources and Evaluation Conference

Natural Language Processing TechniquesTopic Modeling

Cited by 383

Google Scholar: the pros and the cons

Jacsó, P. (2005) · Online Information Review

Information Retrieval and Search BehaviorLibrary Science and Information

Cited by 383

Activity Recognition Using a Single Accelerometer Placed at the Wrist or Ankle

MANNINI, A., INTILLE, S. S., ROSENBERGER, M., SABATINI, A. M., & HASKELL, W. (2013) · Medicine & Science in Sports & Exercise

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 383

The YOLO Framework: A Comprehensive Review of Evolution, Applications, and Benchmarks in Object Detection

Ali, M. L., & Zhang, Z. (2024) · Computers

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 383

When LLMs meet cybersecurity: a systematic literature review

Zhang, J., Bu, H., Wen, H., Liu, Y., Fei, H., Xi, R., Li, L., Yang, Y., Zhu, H., & Meng, D. (2025) · Cybersecurity

Adversarial Robustness in Machine LearningNetwork Security and Intrusion Detection

Cited by 383

Quantum certification and benchmarking

Eisert, J., Hangleiter, D., Walk, N., Roth, I., Markham, D., Parekh, R., Chabaud, U., & Kashefi, E. (2020) · Freie Universität Berlin

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 383

Endmember bundles: a new approach to incorporating endmember variability into spectral mixture analysis

Bateson, C. A., Asner, G. P., & Wessman, C. A. (2000) · IEEE Transactions on Geoscience and Remote Sensing

Remote-Sensing Image ClassificationRemote Sensing in Agriculture

Cited by 382

CNTK: Microsoft's Open-Source Deep-Learning Toolkit

Seide, F., & Agarwal, A. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Neural Networks and ApplicationsAdvanced Neural Network Applications

Cited by 382