Check computer science papers: citations, claims and retractions

Formal verification of the W3C web authentication protocol

Guirat, I. B., & Halpin, H. (2018) · Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security

Advanced Authentication Protocols SecurityFormal Methods in Verification

Cited by 16

A new approach to automatic measure fetal head circumference in ultrasound images using convolutional neural networks

Yang, C., Yang, Z., Liao, S., Guo, J., Yin, S., Liu, C., & Kang, Y. (2022) · Computers in Biology and Medicine

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 16

Classifier Suites for Insider Threat Detection

Noever, D. (2019) · arXiv

Information and Cyber SecurityNetwork Security and Intrusion Detection

Cited by 16

Chain of Thoughtlessness? An Analysis of CoT in Planning

Stechly, K., Valmeekam, K., & Kambhampati, S. (2024) · Advances in Neural Information Processing Systems 37

AI-based Problem Solving and PlanningDecision-Making and Behavioral Economics

Cited by 16

International AI Safety Report

Bengio, Y., Mindermann, S., Privitera, D., Besiroglu, T., Bommasani, R., Casper, S., Choi, Y., Fox, P., Garfinkel, B., Goldfarb, D., et al. (2025) · arXiv

Ethics and Social Impacts of AISafety Systems Engineering in Autonomy

Cited by 16

On pipelines, readiness and annotative labour: Political geographies of AI and data infrastructures in Africa

Holden, K., & Harsh, M. (2024) · Political Geography

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 16

Hidding the Ghostwriters: An Adversarial Evaluation of AI-Generated Student Essay Detection

Peng, X., Zhou, Y., He, B., Sun, L., & Sun, Y. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Adversarial Robustness in Machine LearningAuthorship Attribution and Profiling

Cited by 16

Towards creating specialised integrity checks through partial evaluation of meta-interpreters

Leuschel, M., & De Schreye, D. (1995) · Proceedings of the 1995 ACM SIGPLAN symposium on Partial evaluation and semantics-based program manipulation - PEPM '95

Logic, programming, and type systemsLogic, Reasoning, and Knowledge

Cited by 16

Self-Supervised Video GANs: Learning for Appearance Consistency and Motion Coherency

Hyun, S., Kim, J., & Heo, J.-P. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 16

Incremental and Enhanced Scanline-Based Segmentation Method for Surface Reconstruction of Sparse LiDAR Data

Wang, W., Sakurada, K., & Kawaguchi, N. (2016) · Remote Sensing

3D Shape Modeling and Analysis3D Surveying and Cultural Heritage

Cited by 16

An Empirical Study of Harness Design for Coding Agents

Fan, R.-Z., Zhang, Z., Ma, S., Hu, Y., Wang, S., Song, K., Liu, F., Zamani, H., & Wang, X. (2026) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 16

Learning Weighted Submanifolds With Variational Autoencoders and Riemannian Variational Autoencoders

Miolane, N., & Holmes, S. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Neural Networks and ApplicationsTopological and Geometric Data Analysis

Cited by 16

The Political Economy of Blockchain Governance

Lee, B. E., Moroz, D. J., & Parkes, D. C. (2020) · SSRN Electronic Journal

Blockchain Technology Applications and SecurityGame Theory and Voting Systems

Cited by 16

Multi-particle quantum walks on 3D integrated photonic chip

Zhou, W.-H., Wang, X.-W., Ren, R.-J., Fu, Y.-X., Chang, Y.-J., Xu, X.-Y., Tang, H., & Jin, X.-M. (2024) · Light: Science & Applications

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 16

Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue

Gu, J.-C., Xu, H.-X., Ma, J.-Y., Lu, P., Ling, Z.-H., Chang, K.-W., & Peng, N. (2024) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 16

Designing robots that do no harm: understanding the challenges of Ethics for Robots

Hutler, B., Rieder, T. N., Mathews, D. J. H., Handelman, D. A., & Greenberg, A. M. (2024) · AI and Ethics

Ethics and Social Impacts of AISocial Robot Interaction and HRI

Cited by 16

Quiz Design Task: Helping Teachers Create Quizzes with Automated Question Generation

Laban, P., Wu, C.-S., Murakhovs'ka, L., Liu, W., & Xiong, C. (2022) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 16

The Development of University Students’ Self-Sufficiency Based on Interactive Technologies by Their Immersion in the Professional Activity

Ljubimova, E. M., Galimullina, E. Z., & Ibatullin, R. R. (2015) · International Education Studies

Educational Technology and E-LearningOnline and Blended Learning

Cited by 16

Error tolerance and tradeoffs in loss- and failure-tolerant quantum computing schemes

Rohde, P. P., Ralph, T. C., & Munro, W. J. (2007) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 16

Dynamic Blockchain-Empowered Trustworthy End-Edge Collaborative Computing via Rotating Multi-Agent DRL

Xu, C., Zhang, P., Yu, H., & Li, Y. (2025) · IEEE Transactions on Wireless Communications

Blockchain Technology Applications and SecurityCloud Data Security Solutions

Cited by 16

A 98-qubit trapped-ion quantum computer with all-to-all connectivity

Ransford, A., Allman, M. S., Arkinstall, J., Campora, J. P., Cooper, S. F., Delaney, R. D., Dreiling, J. M., Estey, B., Figgatt, C., Hall, A., et al. (2026) · Nature

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 16

TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs

Gastinger, J., Huang, S., Galkin, M., Loghmani, E., Parviz, A., Poursafaei, F., Danovitch, J., Rossi, E., Koutis, I., Stuckenschmidt, H., et al. (2024) · Advances in Neural Information Processing Systems 37

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 16

Color code decoder with improved scaling for correcting circuit-level noise

Lee, S.-H., Li, A., & Bartlett, S. D. (2025) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 16

Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs

Tie, G., Yuan, Z., Zhao, Z., Hu, C., Gu, T., Zhang, R., Zhang, S., Wu, J., Tu, X., Jin, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 16