Check computer science papers: citations, claims and retractions

Breaking the fidelity barrier: an examination of our current characterization of prototypes and an example of a mixed-fidelity success

McCurdy, M., Connors, C., Pyrzak, G., Kanefsky, B., & Vera, A. (2006) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 192

Internet-Augmented Dialogue Generation

Komeili, M., Shuster, K., & Weston, J. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Speech and dialogue systemsTopic Modeling

Cited by 192

Decoding ChatGPT: A taxonomy of existing research, current challenges, and possible future directions

Sohail, S. S., Farhat, F., Himeur, Y., Nadeem, M., Madsen, D. Ø., Singh, Y., Atalla, S., & Mansoor, W. (2023) · Journal of King Saud University - Computer and Information Sciences

Topic ModelingArtificial Intelligence Applications

Cited by 192

Simulated Annealing Algorithm for Deep Learning

Rere, L. M. R., Fanany, M. I., & Arymurthy, A. M. (2015) · Procedia Computer Science

Stochastic Gradient Optimization TechniquesMetaheuristic Optimization Algorithms Research

Cited by 192

Making knowledge tradable in edge-ai enabled iot: a consortium blockchain-based efficient and incentive approach

Lin, X., Li, J., Wu, J., Liang, H., & Yang, W. (2019) · IEEE Transactions on Industrial Informatics

Blockchain Technology Applications and SecurityIoT and Edge/Fog Computing

Cited by 192

Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain

Hao, J., Yang, T., Tang, H., Bai, C., Liu, J., Meng, Z., Liu, P., & Wang, Z. (2021) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 192

Picbreeder: evolving pictures collaboratively online

Secretan, J., Beato, N., D Ambrosio, D. B., Rodriguez, A., Campbell, A., & Stanley, K. O. (2008) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Evolutionary Algorithms and ApplicationsArt, Technology, and Culture

Cited by 192

Multiband Spectrum Sensing and Resource Allocation for IoT in Cognitive 5G Networks

Ejaz, W., & Ibnkahla, M. (2018) · IEEE Internet of Things Journal

Cognitive Radio Networks and Spectrum SensingIoT Networks and Protocols

Cited by 191

Analyzing Data Granularity Levels for Insider Threat Detection Using Machine Learning

Le, D. C., Zincir-Heywood, N., & Heywood, M. I. (2020) · IEEE Transactions on Network and Service Management

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 191

PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning

Garrett, C. R., Lozano-Pérez, T., & Kaelbling, L. P. (2020) · Proceedings of the International Conference on Automated Planning and Scheduling

AI-based Problem Solving and PlanningRobotic Path Planning Algorithms

Cited by 191

Countering Malicious DeepFakes: Survey, Battleground, and Horizon

Juefei-Xu, F., Wang, R., Huang, Y., Guo, Q., Ma, L., & Liu, Y. (2022) · International Journal of Computer Vision

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 191

Adiabatic Quantum Simulation of Quantum Chemistry

Babbush, R., Love, P. J., & Aspuru-Guzik, A. (2014) · Scientific Reports

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 191

Mobility-Aware Cooperative Caching in Vehicular Edge Computing Based on Asynchronous Federated and Deep Reinforcement Learning

Wu, Q., Zhao, Y., Fan, Q., Fan, P., Wang, J., & Zhang, C. (2023) · IEEE Journal of Selected Topics in Signal Processing

Caching and Content DeliveryIoT and Edge/Fog Computing

Cited by 191

IEEE Standard for Information technology--Telecommunications and information exchange between systems--Local and metropolitan area networks--Specific requirements-Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 3: Enhancements for Very High Throughput in the 60 GHz Band

(2012)

Wireless Networks and ProtocolsMillimeter-Wave Propagation and Modeling

Cited by 191

3D multi-view convolutional neural networks for lung nodule classification

Kang, G., Liu, K., Hou, B., & Zhang, N. (2017) · PLOS ONE

AI in cancer detectionLung Cancer Diagnosis and Treatment

Cited by 191

What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?

Mayer, N., Ilg, E., Fischer, P., Hazirbas, C., Cremers, D., Dosovitskiy, A., & Brox, T. (2018) · International Journal of Computer Vision

Advanced Vision and ImagingAdvanced Neural Network Applications

Cited by 191

Reflecting on the think‐aloud method for evaluating e‐learning

Cotton, D., & Gresty, K. (2006) · British Journal of Educational Technology

Usability and User Interface DesignEducational Research and Methods

Cited by 191

Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes

Papagiannidis, E., Enholm, I. M., Dremel, C., Mikalef, P., & Krogstie, J. (2023) · Information Systems Frontiers

Ethics and Social Impacts of AIInformation Technology Governance and Strategy

Cited by 191

Deep learning of transferable representation for scalable domain adaptation

Long, M., Wang, J., Cao, Y., Sun, J., & Yu, P. S. (2016) · IEEE Transactions on Knowledge and Data Engineering

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 191

Automatic Prompt Optimization with “Gradient Descent” and Beam Search

Pryzant, R., Iter, D., Li, J., Lee, Y., Zhu, C., & Zeng, M. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 191

Achieving quantum supremacy with sparse and noisy commuting quantum computations

Bremner, M. J., Montanaro, A., & Shepherd, D. J. (2017) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 191

Using GitHub Copilot to Solve Simple Programming Problems

Wermelinger, M. (2023) · Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1

Teaching and Learning ProgrammingSoftware Engineering Research

Cited by 191

FABRIC: A National-Scale Programmable Experimental Network Infrastructure

Baldin, I., Nikolich, A., Griffioen, J., Monga, I. I. S., Wang, K.-C., Lehman, T., & Ruth, P. (2019) · IEEE Internet Computing

Software-Defined Networks and 5GDistributed and Parallel Computing Systems

Cited by 191

The successor representation: Its computational logic and neural substrates

Gershman, S. J. (2018) · The Journal of Neuroscience

Reinforcement Learning in RoboticsMemory and Neural Mechanisms

Cited by 191