Check computer science papers: citations, claims and retractions

CacheBlend: Fast Large Language Model Serving for RAG with Cached Knowledge Fusion

Yao, J., Li, H., Liu, Y., Ray, S., Cheng, Y., Zhang, Q., Du, K., Lu, S., & Jiang, J. (2025) · Proceedings of the Twentieth European Conference on Computer Systems

Topic ModelingNatural Language Processing Techniques

Cited by 75

Blockchain for Securing AI Applications and Open Innovations

Shinde, R., Patil, S., Kotecha, K., & Ruikar, K. (2021) · Journal of Open Innovation: Technology, Market, and Complexity

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 75

True Random Number Generator circuits based on single- and multi-phase beat frequency detection

Tang, Q., Kim, B., Lao, Y., Parhi, K. K., & Kim, C. H. (2014) · Proceedings of the IEEE 2014 Custom Integrated Circuits Conference

Physical Unclonable Functions (PUFs) and Hardware SecurityAdvancements in PLL and VCO Technologies

Cited by 75

Visualizing Student Opinion Through Text Analysis

Cunningham-Nelson, S., Baktashmotlagh, M., & Boles, W. (2019) · IEEE Transactions on Education

Sentiment Analysis and Opinion MiningOnline Learning and Analytics

Cited by 75

Randomness testing of the advanced encryption standard finalist candidates

Soto, J., & Bassham, L. (2000)

Cryptographic Implementations and SecurityChaos-based Image/Signal Encryption

Cited by 75

A systematic review on machine learning models for online learning and examination systems

Kaddoura, S., Popescu, D. E., & Hemanth, J. D. (2022) · PeerJ Computer Science

Online Learning and AnalyticsArtificial Intelligence in Education

Cited by 75

Five Challenges for Intelligent Text Entry Methods

Kristensson, P. O., & Jameson, A. (2009) · AI Magazine

Usability and User Interface DesignGaze Tracking and Assistive Technology

Cited by 75

Medical image analysis: computer-aided diagnosis of gastric cancer invasion on endoscopic images

Kubota, K., Kuroda, J., Yoshida, M., Ohta, K., & Kitajima, M. (2012) · Surgical Endoscopy

AI in cancer detectionGastric Cancer Management and Outcomes

Cited by 75

A Framework for Assurance Audits of Algorithmic Systems

Lam, K., Lange, B., Blili-Hamelin, B., Davidovic, J., Brown, S., & Hasan, A. (2024) · The 2024 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 75

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos

Baker, B., Akkaya, I., Zhokhov, P., Huizinga, J., Tang, J., Ecoffet, A., Houghton, B., Sampedro, R., & Clune, J. (2022) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 75

How Visualizing Inferential Uncertainty Can Mislead Readers About Treatment Effects in Scientific Results

Hofman, J. M., Goldstein, D. G., & Hullman, J. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Data Visualization and AnalyticsDecision-Making and Behavioral Economics

Cited by 75

The tao of inference in privacy-protected databases

Bindschaedler, V., Grubbs, P., Cash, D., Ristenpart, T., & Shmatikov, V. (2018) · Proceedings of the VLDB Endowment

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 75

Fibonacci Q-Matrix, Hyperchaos, and Galois Field (2⁸) for Augmented Medical Image Encryption

El-Damak, D., Alexan, W., Mamdouh, E., El-Aasser, M., Fathy, A., & Gabr, M. (2024) · IEEE Access

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 75

Evaluating Explainable Artificial Intelligence (XAI) techniques in chest radiology imaging through a human-centered Lens

E. Ihongbe, I., Fouad, S., F. Mahmoud, T., Rajasekaran, A., & Bhatia, B. (2024) · PLOS ONE

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 75

Distributed Multi-Cloud Multi-Access Edge Computing by Multi-Agent Reinforcement Learning

Zhang, Y., Di, B., Zheng, Z., Lin, J., & Song, L. (2021) · IEEE Transactions on Wireless Communications

IoT and Edge/Fog ComputingCloud Computing and Resource Management

Cited by 75

Enhancing IoT anomaly detection performance for federated learning

Weinger, B., Kim, J., Sim, A., Nakashima, M., Moustafa, N., & Wu, K. J. (2022) · Digital Communications and Networks

Privacy-Preserving Technologies in DataAnomaly Detection Techniques and Applications

Cited by 75

Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Yetiştiren, B., Özsoy, I., Ayerdem, M., & Tüzün, E. (2023) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 75

On User-Centric Modular QoE Prediction for VoIP Based on Machine-Learning Algorithms

Charonyktakis, P., Plakia, M., Tsamardinos, I., & Papadopouli, M. (2016) · IEEE Transactions on Mobile Computing

Image and Video Quality AssessmentNetwork Traffic and Congestion Control

Cited by 75

Do Large Language Models Know What They Don't Know?

Yin, Z., Sun, Q., Guo, Q., Wu, J., Qiu, X., & Huang, X. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 75

TransMS: Knowledge Graph Embedding for Complex Relations by Multidirectional Semantics

Yang, S., Tian, J., Zhang, H., Yan, J., He, H., & Jin, Y. (2019) · Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

Advanced Graph Neural NetworksTopic Modeling

Cited by 75

Effects of personalised feedback approach on knowledge building, emotions, co-regulated behavioural patterns and cognitive load in online collaborative learning

Zheng, L., Zhong, L., & Niu, J. (2022) · Assessment & Evaluation in Higher Education

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 75

Genetic algorithms for generation of class boundaries

Pal, S. K., Bandyopadhyay, S., & Murthy, C. A. (1998) · IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)

Evolutionary Algorithms and ApplicationsMetaheuristic Optimization Algorithms Research

Cited by 75

The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning

Ye, X., & Durrett, G. (2022) · Advances in Neural Information Processing Systems 35

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 75

Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination

Wu, M., Zhang, Z., Dong, Q., Xi, Z., Zhao, J., Jin, S., Fan, X., Zhou, Y., Lv, H., Zhang, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 75