Check computer science papers: citations, claims and retractions

Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing

Vinciarelli, A., Pantic, M., Heylen, D., Pelachaud, C., Poggi, I., D'Errico, F., & Schroeder, M. (2012) · IEEE Transactions on Affective Computing

Emotion and Mood RecognitionSocial Robot Interaction and HRI

Cited by 381

Gender bias and stereotypes in Large Language Models

Kotek, H., Dockum, R., & Sun, D. (2023) · Proceedings of The ACM Collective Intelligence Conference

Ethics and Social Impacts of AITopic Modeling

Cited by 381

Exploring Simple Siamese Representation Learning

Chen, X., & He, K. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 381

Mathematical foundation of quantum annealing

Morita, S., & Nishimori, H. (2008) · Journal of Mathematical Physics

Quantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications

Cited by 381

Experiencing algorithms: How young people understand, feel about, and engage with algorithmic news selection on social media

Swart, J. (2021) · Social Media + Society

Ethics and Social Impacts of AISocial Media and Politics

Cited by 381

3D Menagerie: Modeling the 3D Shape and Pose of Animals

Zuffi, S., Kanazawa, A., Jacobs, D. W., & Black, M. J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisFace recognition and analysis

Cited by 381

A robust privacy-preserving federated learning model against model poisoning attacks

Yazdinejad, A., Dehghantanha, A., Karimipour, H., Srivastava, G., & Parizi, R. M. (2024) · IEEE Transactions on Information Forensics and Security

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 380

KBA: kernel boundary alignment considering imbalanced data distribution

Wu, G., & Chang, E. Y. (2005) · IEEE Transactions on Knowledge and Data Engineering

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 380

Data Mining: Statistics and More?

Hand, D. J. (1998) · The American Statistician

Data Mining Algorithms and ApplicationsData Mining and Machine Learning Applications

Cited by 380

A Unified Framework of Five Principles for AI in Society

Floridi, L., & Cowls, J. (2022) · Machine Learning and the City

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 380

Language style matching in writing: synchrony in essays, correspondence, and poetry.

Ireland, M. E., & Pennebaker, J. W. (2010) · Journal of Personality and Social Psychology

Authorship Attribution and ProfilingMental Health via Writing

Cited by 380

What do we talk about when we talk about dashboards?

Sarikaya, A., Correll, M., Bartram, L., Tory, M., & Fisher, D. (2019) · IEEE Transactions on Visualization and Computer Graphics

Data Visualization and AnalyticsComputer Graphics and Visualization Techniques

Cited by 380

Energy-Efficient Cooperative Relaying over Fading Channels with Simple Relay Selection

Madan, R., Mehta, N., Molisch, A., & Zhang, J. (2008) · IEEE Transactions on Wireless Communications

Cooperative Communication and Network CodingMobile Ad Hoc Networks

Cited by 380

Viewpoint: Human-in-the-loop Artificial Intelligence

Zanzotto, F. M. (2019) · Journal of Artificial Intelligence Research

Ethics and Social Impacts of AILaw, AI, and Intellectual Property

Cited by 380

Graph-to-Sequence Learning using Gated Graph Neural Networks

Beck, D., Haffari, G., & Cohn, T. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Advanced Graph Neural NetworksTopic Modeling

Cited by 380

Voice acoustic measures of depression severity and treatment response collected via interactive voice response (IVR) technology

Mundt, J. C., Snyder, P. J., Cannizzaro, M. S., Chappie, K., & Geralts, D. S. (2007) · Journal of Neurolinguistics

Emotion and Mood RecognitionVoice and Speech Disorders

Cited by 380

Integrated multimodal artificial intelligence framework for healthcare applications

Soenksen, L. R., Ma, Y., Zeng, C., Boussioux, L., Villalobos Carballo, K., Na, L., Wiberg, H. M., Li, M. L., Fuentes, I., & Bertsimas, D. (2022) · npj Digital Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 380

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Zhou, D., Schärli, N., Hou, L., Wei, J., Scales, N., Wang, X., Schuurmans, D., Cui, C., Bousquet, O., Le, Q., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 380

Key Reinstallation Attacks: Forcing Nonce Reuse in WPA2

Vanhoef, M., & Piessens, F. (2017) · Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security

Cryptographic Implementations and SecurityAdvanced Authentication Protocols Security

Cited by 380

Gaussian Temporal Awareness Networks for Action Localization

Long, F., Yao, T., Qiu, Z., Tian, X., Luo, J., & Mei, T. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 380

Data integration enables global biodiversity synthesis

Heberling, J. M., Miller, J. T., Noesgaard, D., Weingart, S. B., & Schigel, D. (2021) · Proceedings of the National Academy of Sciences

Research Data Management PracticesSpecies Distribution and Climate Change

Cited by 380

A modified split-radix fft with fewer arithmetic operations

Johnson, S. G., & Frigo, M. (2007) · IEEE Transactions on Signal Processing

Digital Filter Design and ImplementationMathematical Analysis and Transform Methods

Cited by 380

Computer-aided detection of breast Cancer on mammograms: a swarm intelligence optimized wavelet neural network approach

Dheeba, J., Albert Singh, N., & Tamil Selvi, S. (2014) · Journal of Biomedical Informatics

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 380

ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection

Yamagishi, J., Wang, X., Todisco, M., Sahidullah, M., Patino, J., Nautsch, A., Liu, X., Lee, K. A., Kinnunen, T., Evans, N., et al. (2021) · 2021 Edition of the Automatic Speaker Verification and Spoofing Countermeasures Challenge

Speech Recognition and SynthesisBiometric Identification and Security

Cited by 380