Check computer science papers: citations, claims and retractions

The effect of Twitter on college student engagement and grades: Twitter and student engagement

Junco, R., Heiberger, G., & Loken, E. (2011) · Journal of Computer Assisted Learning

Educational Technology in LearningOnline and Blended Learning

Cited by 1,535

Visualizing the effects of predictor variables in black box supervised learning models

Apley, D. W., & Zhu, J. (2020) · Journal of the Royal Statistical Society Series B: Statistical Methodology

Explainable Artificial Intelligence (XAI)Data Visualization and Analytics

Cited by 1,535

Target-driven visual navigation in indoor scenes using deep reinforcement learning

Zhu, Y., Mottaghi, R., Kolve, E., Lim, J. J., Gupta, A., Fei-Fei, L., & Farhadi, A. (2017) · 2017 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 1,533

Knowledge vault: a web-scale approach to probabilistic knowledge fusion

Dong, X., Gabrilovich, E., Heitz, G., Horn, W., Lao, N., Murphy, K., Strohmann, T., Sun, S., & Zhang, W. (2014) · Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining

Semantic Web and OntologiesTopic Modeling

Cited by 1,533

Encoding a qubit in an oscillator

Gottesman, D., Kitaev, A., & Preskill, J. (2001) · Physical Review A

Quantum Information and CryptographyQuantum Computing Algorithms and Architecture

Cited by 1,532

Data quality in online human-subjects research: Comparisons between MTurk, Prolific, CloudResearch, Qualtrics, and SONA

Douglas, B. D., Ewell, P. J., & Brauer, M. (2023) · PLOS ONE

Mobile Crowdsensing and CrowdsourcingSurvey Methodology and Nonresponse

Cited by 1,532

Discrete Signal Processing on Graphs

Sandryhaila, A., & Moura, J. M. F. (2013) · IEEE Transactions on Signal Processing

Advanced Graph Neural NetworksMathematical Analysis and Transform Methods

Cited by 1,531

Why Hackers Do What They Do: Understanding Motivation and Effort in Free/Open Source Software Projects

Lakhani, K. R., & Wolf, R. G. (2003) · The MIT Press eBooks

Open Source Software InnovationsSoftware Engineering Techniques and Practices

Cited by 1,531

Logarithmic Negativity: A Full Entanglement Monotone That is not Convex

Plenio, M. B. (2005) · Physical Review Letters

Quantum Information and CryptographyQuantum Mechanics and Applications

Cited by 1,530

Character-Aware Neural Language Models

Kim, Y., Jernite, Y., Sontag, D., & Rush, A. M. (2015) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 1,530

Why Hackers Do What They Do: Understanding Motivation and Effort in Free/Open Source Software Projects

Lakhani, K. R., & Wolf, R. G. (2005) · Perspectives on Free and Open Source Software

Open Source Software InnovationsSoftware Engineering Techniques and Practices

Cited by 1,530

Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition

Sharif, M., Bhagavatula, S., Bauer, L., & Reiter, M. K. (2016) · Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 1,530

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Frankle, J., & Carbin, M. (2018) · arXiv

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 1,529

Bulk Spin-Resonance Quantum Computation

Gershenfeld, N. A., & Chuang, I. L. (1997) · Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,528

Content-based multimedia information retrieval: State of the art and challenges

Lew, M. S., Sebe, N., Djeraba, C., & Jain, R. (2006) · ACM Transactions on Multimedia Computing, Communications, and Applications

Image Retrieval and Classification TechniquesVideo Analysis and Summarization

Cited by 1,528

Things That Make Us Smart: Defending Human Attributes in the Age of the Machine

Robinson, R., & Norman, D. (1994) · Design Issues

Innovative Human-Technology InteractionCybernetics and Technology in Society

Cited by 1,528

Sparks of Artificial General Intelligence: Early experiments with GPT-4

Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y. T., Li, Y., Lundberg, S., et al. (2023) · arXiv

Topic ModelingArtificial Intelligence Applications

Cited by 1,526

Universal quantum computation with ideal Clifford gates and noisy ancillas

Bravyi, S., & Kitaev, A. (2005) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,525

ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation

Vu, T.-H., Jain, H., Bucher, M., Cord, M., & Perez, P. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 1,524

Relation Networks for Object Detection

Hu, H., Gu, J., Zhang, Z., Dai, J., & Wei, Y. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 1,524

Reversible Computing

Toffoli, T. (1980) · Lecture Notes in Computer Science

Quantum-Dot Cellular AutomataCellular Automata and Applications

Cited by 1,523

Privacy in the age of medical big data

Price, W. N., & Cohen, I. G. (2019) · Nature Medicine

Thoreau and American LiteratureEthics in Clinical Research

Cited by 1,522

Software for molecular docking: a review

Pagadala, N. S., Syed, K., & Tuszynski, J. (2017) · Biophysical Reviews

Computational Drug Discovery MethodsProtein Structure and Dynamics

Cited by 1,522

From learning models of natural image patches to whole image restoration

Zoran, D., & Weiss, Y. (2011) · 2011 International Conference on Computer Vision

Image and Signal Denoising MethodsAdvanced Image Processing Techniques

Cited by 1,522