Check computer science papers: citations, claims and retractions

An improved Bülban map and its application in multiple image encryption

Shabasy, N. H. E., Mansy, A., & Alexan, W. (2026) · Journal of King Saud University Computer and Information Sciences

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 9

Clarifying False Memories in Voice-based Search

Kiesel, J., Bahrami, A., Stein, B., Anand, A., & Hagen, M. (2019) · Proceedings of the 2019 Conference on Human Information Interaction and Retrieval

Information Retrieval and Search BehaviorSpeech and dialogue systems

Cited by 9

Personalized Federated Learning of Driver Prediction Models for Autonomous Driving

Nakanoya, M., Im, J., Qiu, H., Katti, S., Pavone, M., & Chinchali, S. (2021) · arXiv

Privacy-Preserving Technologies in DataAutonomous Vehicle Technology and Safety

Cited by 9

FedRSC: A Federated Learning Analysis for Multi-Label Road Surface Classifications

Vondikakis, I. V., Panagiotopoulos, I. E., & Dimitrakopoulos, G. J. (2024) · IEEE Open Journal of Intelligent Transportation Systems

Privacy-Preserving Technologies in DataInfrastructure Maintenance and Monitoring

Cited by 9

Elaboration on an integrated architecture and requirement practice: Prototyping with quality attribute focus

Bellomo, S., Nord, R. L., & Ozkaya, I. (2013) · 2013 2nd International Workshop on the Twin Peaks of Requirements and Architecture (TwinPeaks)

Software Engineering Techniques and PracticesAdvanced Software Engineering Methodologies

Cited by 9

Multimodal Data Fusion based on the Global Workspace Theory

Bao, C., Fountas, Z., Olugbade, T., & Bianchi-Berthouze, N. (2020) · arXiv

Multimodal Machine Learning ApplicationsEmotion and Mood Recognition

Cited by 9

Humans or LLMs as the Judge? A Study on Judgement Biases

Chen, G. H., Chen, S., Liu, Z., Jiang, F., & Wang, B. (2024) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 9

Democratizing LLMs: An Exploration of Cost-Performance Trade-offs in Self-Refined Open-Source Models

Shashidhar, S., Chinta, A., Sahai, V., Wang, Z., & Ji, H. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Topic ModelingNatural Language Processing Techniques

Cited by 9

IdeaBench: Benchmarking Large Language Models for Research Idea Generation

Guo, S., Shariatmadari, A. H., Xiong, G., Huang, A., Kim, M., Williams, C. M., Bekiranov, S., & Zhang, A. (2025) · Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2

Topic ModelingArtificial Intelligence Applications

Cited by 9

Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading

Chen, H., Pasunuru, R., Weston, J., & Celikyilmaz, A. (2023) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 9

Security and Quality in LLM-Generated Code: A Multi-Language, Multi-Model Analysis

Kharma, M. F., Choi, S., Alkhanafseh, M., & Mohaisen, D. (2026) · IEEE Transactions on Dependable and Secure Computing

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 9

Using Ultrasonic Haptics Within an Immersive Spider Exposure Environment to Provide a Multi-Sensorial Experience

Brice, D., Gibson, Z., McGuinness, F., & Rafferty, K. (2021) · Frontiers in Virtual Reality

Virtual Reality Applications and ImpactsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Cited by 9

Algebraically rigorous quaternion framework for the neural network pose estimation problem

Lin, C., Hanson, A. J., & Hanson, S. M. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

3D Shape Modeling and AnalysisAlgebraic and Geometric Analysis

Cited by 9

Are Large Language Model Temporally Grounded?

Qiu, Y., Zhao, Z., Ziser, Y., Korhonen, A., Ponti, E., & Cohen, S. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 9

DistillSpec: Improving Speculative Decoding via Knowledge Distillation

Zhou, Y., Lyu, K., Rawat, A. S., Menon, A. K., Rostamizadeh, A., Kumar, S., Kagy, J.-F., & Agarwal, R. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 9

Eliminating the Effect of Rating Bias on Reputation Systems

Wu, L., Ren, Z., Ren, X.-L., Zhang, J., & Lü, L. (2018) · Complexity

Recommender Systems and TechniquesAccess Control and Trust

Cited by 9

COBART: Controlled, Optimized, Bidirectional and Auto-Regressive Transformer for Ad Headline Generation

Kanungo, Y. S., Das, G., A, P., & Negi, S. (2022) · Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Topic ModelingInformation Retrieval and Search Behavior

Cited by 9

Magic state cultivation: growing T states as cheap as CNOT gates

Gidney, C., Shutty, N., & Jones, C. (2024) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 9

A human in the loop: AI won’t surpass human intelligence anytime soon

Brooks, R. (2021) · IEEE Spectrum

Artificial Intelligence ApplicationsCybernetics and Technology in Society

Cited by 9

Can Fans Build Parasocial Relationships through Idols' Simulated Voice Messages?: A Study of AI Private Call Users' Perceptions, Cognitions, and Behaviors

Kang, E. J., Kim, H., Kim, H., Fussell, S. R., & Kim, J. (2025) · Proceedings of the ACM on Human-Computer Interaction

Innovative Human-Technology InteractionSocial Robot Interaction and HRI

Cited by 9

A memristive computational neural network model for time-series processing

Pistolesi, V., Ceni, A., Milano, G., Ricciardi, C., & Gallicchio, C. (2025) · APL Machine Learning

Neural Networks and Reservoir ComputingAdvanced Memory and Neural Computing

Cited by 9

An Explorative Analysis of the Feasibility of Implementing Metacognitive Strategies in Self-Regulated Learning with the Conversational Agents

Desai, S., & Chin, J. (2020) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting

Intelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning Methods

Cited by 9

Toward Uncertainty Quantification for Supervised Classification

Sandia National Laboratories (SNL-NM), A., Darling, M., (NNSA), U. N. N. S. A., & Stracuzzi, D. (2018)

Adversarial Robustness in Machine LearningMachine Learning and Data Classification

Cited by 9

Endoscopic Navigation in the Clinic: Registration in the Absence of Preoperative Imaging

Sinha, A., Ishii, M., Hager, G. D., & Taylor, R. H. (2019) · International Journal of Computer Assisted Radiology and Surgery

Medical Image Segmentation TechniquesAnatomy and Medical Technology

Cited by 9