Check computer science papers: citations, claims and retractions

Explainable AI: enhancing decision-making in the detection of cyber threats

Prasad, P. W. C., Sayeed, M. S., Nguyen, D.-M., Hutabarat, D. P., & Mohiuddin, G. M. (2026) · Frontiers in Computer Science

Explainable Artificial Intelligence (XAI)Network Security and Intrusion Detection

Cited by 16

Admissions in the age of AI: detecting AI-generated application materials in higher education

Zhao, Y., Borelli, A., Martinez, F., Xue, H., & Weiss, G. M. (2024) · Scientific Reports

Authorship Attribution and ProfilingArtificial Intelligence in Education

Cited by 16

Are Large Language Models Memorizing Bug Benchmarks?

Ramos, D., Mamede, C., Jain, K., Canelas, P., Gamboa, C., & Goues, C. L. (2024) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 16

Prick “filter bubbles” by enhancing consumers’ novelty-seeking: The role of personalized recommendations of unmentionable products

Lv, L., Kang, K. Q., & Liu, G. (. (2024) · Psychology & Marketing

Recommender Systems and TechniquesDigital Marketing and Social Media

Cited by 16

Crowd Density Forecasting by Modeling Patch-Based Dynamics

Minoura, H., Yonetani, R., Nishimura, M., & Ushiku, Y. (2021) · IEEE Robotics and Automation Letters

Video Surveillance and Tracking MethodsEvacuation and Crowd Dynamics

Cited by 16

A framework enabling LLMs into regulatory environment for transparency and trustworthiness and its application to drug labeling document

Wu, L., Xu, J., Thakkar, S., Gray, M., Qu, Y., Li, D., & Tong, W. (2024) · Regulatory Toxicology and Pharmacology

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 16

Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Varshney, N., & Baral, C. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 16

Estimating Cognitive Load in a Mobile Personal Health Record Application: A Cognitive Task Analysis Approach

Zayim, N., Yıldız, H., & Yüce, Y. K. (2023) · Healthcare Informatics Research

Usability and User Interface DesignMobile Health and mHealth Applications

Cited by 16

Efficient approximation of experimental Gaussian boson sampling

Villalonga, B., Niu, M. Y., Li, L., Neven, H., Platt, J. C., Smelyanskiy, V. N., & Boixo, S. (2021) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 16

What's to Know? Uncertainty as a Guide to Asking Goal-Oriented Questions

Abbasnejad, E., Wu, Q., Shi, Q., & van den Hengel, A. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Speech and dialogue systemsMultimodal Machine Learning Applications

Cited by 16

Deep Transductive Transfer Regression Network for Cross-Corpus Speech Emotion Recognition

Zhao, Y., Wang, J., Ye, R., Zong, Y., Zheng, W., & Zhao, L. (2022) · Interspeech 2022

Emotion and Mood RecognitionSpeech Recognition and Synthesis

Cited by 16

QGEval: Benchmarking Multi-dimensional Evaluation for Question Generation

Fu, W., Wei, B., Hu, J., Cai, Z., & Liu, J. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 16

Beyond explicit feedback: new directions in adaptive collaborative learning support

Walker, E., Rummel, N., & Koedinger, K. R. (2009) · Proceedings of the 9th international conference on Computer supported collaborative learning - CSCL'09

Intelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning Methods

Cited by 16

MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation

Zhang, Z., Wang, Z., Ma, T., Taneja, V. S., Nelson, S., Le, N. H. L., Murugesan, K., Ju, M., Chawla, N. V., Zhang, C., et al. (2025) · Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1

Recommender Systems and TechniquesInnovation in Digital Healthcare Systems

Cited by 16

Mitigations on Sybil-Based Double-Spend Attacks in Bitcoin

Zhang, S., & Lee, J.-H. (2021) · IEEE Consumer Electronics Magazine

Blockchain Technology Applications and SecurityCryptography and Data Security

Cited by 16

The Effects of Working Memory during Search Tasks of Varying Complexity

Choi, B., Capra, R., & Arguello, J. (2019) · Proceedings of the 2019 Conference on Human Information Interaction and Retrieval

Information Retrieval and Search BehaviorUsability and User Interface Design

Cited by 16

Enhancing Security Operations Center: Wazuh Security Event Response with Retrieval-Augmented-Generation-Driven Copilot

Ismail, Kurnia, R., Widyatama, F., Wibawa, I. M., Brata, Z. A., Ukasyah, Nelistiani, G. A., & Kim, H. (2025) · Sensors

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 16

A Part-of-speech tagger for Irish using Finite-State Morphology and Constraint Grammar Disambiguation

Uí Dhonnchadha, E., & Van Genabith, J. (2006) · Proceedings of the Language Resources and Evaluation Conference

Natural Language Processing TechniquesSpeech and dialogue systems

Cited by 16

A hybrid trust model using reinforcement learning and fuzzy logic

Aref, A., & Tran, T. (2018) · Computational Intelligence

Access Control and TrustMulti-Agent Systems and Negotiation

Cited by 16

Carbon efficient VM placement and migration technique for green federated cloud datacenters

Wadhwa, B., & Verma, A. (2014) · 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Cloud Computing and Resource ManagementEnergy Efficiency in Computing

Cited by 16

Rhetorical Figure Detection: the Case of Chiasmus

Dubremetz, M., & Nivre, J. (2015) · Proceedings of the Fourth Workshop on Computational Linguistics for Literature

Natural Language Processing TechniquesTopic Modeling

Cited by 16

Tool, tutor, or crutch?: A grounded theory of cognitive scaffolding and offloading in AI-assisted programming education

Liu, D., Fan, G., & Pan, L. (2026) · International Journal of STEM Education

Teaching and Learning ProgrammingIntelligent Tutoring Systems and Adaptive Learning

Cited by 16

Impact of Voice Fidelity on Decision Making: A Potential Dark Pattern?

Dubiel, M., Sergeeva, A., & Leiva, L. A. (2024) · Proceedings of the 29th International Conference on Intelligent User Interfaces

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 16

Machine learning–based prediction for high health care utilizers by using a multi-institutional diabetes registry: model training and evaluation

Tan, J. K., Quan, L., Salim, N. N. M., Tan, J. H., Goh, S.-Y., Thumboo, J., & Bee, Y. M. (2024) · JMIR AI

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 16