Check computer science papers: citations, claims and retractions

Automating medical simulations

Gershov, S., Braunold, D., Spektor, R., Ioscovich, A., Raz, A., & Laufer, S. (2023) · Journal of Biomedical Informatics

Context-Aware Activity Recognition SystemsSimulation-Based Education in Healthcare

Cited by 8

DeepGuard: Backdoor Attack Detection and Identification Schemes in Privacy-Preserving Deep Neural Networks

Chen, C., Wei, L., Zhang, L., Peng, Y., & Ning, J. (2022) · Security and Communication Networks

Adversarial Robustness in Machine LearningCryptography and Data Security

Cited by 8

Barriers to collaborative information seeking in organizations

Karunakaran, A., & Reddy, M. (2012) · Proceedings of the American Society for Information Science and Technology

Information Retrieval and Search BehaviorLibrary Science and Information Literacy

Cited by 8

A Joint Dependency Model of Morphological and Syntactic Structure for Statistical Machine Translation

Sennrich, R., & Haddow, B. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesSpeech Recognition and Synthesis

Cited by 8

Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine

Bergquist, T., Schaffter, T., Yan, Y., Yu, T., Prosser, J., Gao, J., Chen, G., Charzewski, Ł., Nawalany, Z., Brugere, I., et al. (2023) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 8

Introduction to Soar

Laird, J. E. (2022) · arXiv

AI-based Problem Solving and PlanningPsychiatry, Mental Health, Neuroscience

Cited by 8

Unsupervised deep learning of electronic health records to characterize heterogeneity across Alzheimer disease and related dementias: cross-sectional study

West, M., Cheng, Y., He, Y., Leng, Y., Magdamo, C., Hyman, B. T., Dickson, J. R., Serrano-Pozo, A., Blacker, D., & Das, S. (2025) · JMIR Aging

Machine Learning in HealthcareDementia and Cognitive Impairment Research

Cited by 8

Explainable vs. Interpretable Artificial Intelligence Frameworks in Oncology

Bertsimas, D., & Margonis, G. A. (2023) · Translational Cancer Research

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

Cited by 8

Dataset of Natural Language Queries for E-Commerce

Papenmeier, A., Kern, D., Hienert, D., Sliwa, A., Aker, A., & Fuhr, N. (2021) · Proceedings of the 2021 Conference on Human Information Interaction and Retrieval

Information Retrieval and Search BehaviorNatural Language Processing Techniques

Cited by 8

AQuA: A Benchmarking Tool for Label Quality Assessment

Goswami, M., Sanil, V., Choudhry, A., Srinivasan, A., Udompanyawit, C., & Dubrawski, A. (2023) · arXiv

Machine Learning and Data ClassificationText and Document Classification Technologies

Cited by 8

Unsupervised Active Visual Search With Monte Carlo Planning Under Uncertain Detections

Taioli, F., Giuliari, F., Wang, Y., Berra, R., Castellini, A., Bue, A. D., Farinelli, A., Cristani, M., & Setti, F. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 8

Look, Read and Enrich - Learning from Scientific Figures and their Captions

Gomez-Perez, J. M., & Ortega, R. (2019) · Proceedings of the 10th International Conference on Knowledge Capture

Multimodal Machine Learning ApplicationsHandwritten Text Recognition Techniques

Cited by 8

Human-LLM Coevolution: Evidence from Academic Writing

Geng, M., & Trotta, R. (2025) · Findings of the Association for Computational Linguistics: ACL 2025

Authorship Attribution and ProfilingAcademic integrity and plagiarism

Cited by 8

Multi-indicators prediction in microservice using Granger causality test and Attention LSTM

Ji, S., Wu, W., & Pu, Y. (2020) · 2020 IEEE World Congress on Services (SERVICES)

Software System Performance and ReliabilityTime Series Analysis and Forecasting

Cited by 8

Trust4App: Automating Trustworthiness Assessment of Mobile Applications

Habib, S. M., Alexopoulos, N., Islam, M. M., Heider, J., Marsh, S., & Muehlhaeuser, M. (2018) · 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)

Advanced Malware Detection TechniquesSecurity and Verification in Computing

Cited by 8

PIFR: A novel approach for analyzing pose angle-based human activity to automate fall detection in videos

Kong, V., Soeng, S., Thon, M., Cho, W.-S., Nayyar, A., & Kim, T.-K. (2025) · PLOS One

Context-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Cited by 8

User guide for NIST Media Forensic Challenge (MFC) datasets

Guan, H., Delgado, A., Lee, Y., Yates, A. N., Zhou, D., Kheyrkhah, T., & Fiscus, J. (2021)

Digital Media Forensic DetectionAdvanced Steganography and Watermarking Techniques

Cited by 8

One fish, two fish, but not the whole sea: Alignment reduces language models' conceptual diversity

Murthy, S. K., Ullman, T., & Hu, J. (2025) · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 8

Random Silicon Sampling: Simulating Human Sub-Population Opinion Using a Large Language Model Based on Group-Level Demographic Information

Sun, S., Lee, E., Nan, D., Zhao, X., Lee, W., Jansen, B. J., & Kim, J. H. (2024) · arXiv

Ethics and Social Impacts of AISentiment Analysis and Opinion Mining

Cited by 8

Efficient and Robust Model Benchmarks with Item Response Theory and Adaptive Testing

Song, H., & Flach, P. (2021) · International Journal of Interactive Multimedia and Artificial Intelligence

Machine Learning and Data ClassificationPsychometric Methodologies and Testing

Cited by 8

Efficient LLM Safety Evaluation through Multi-Agent Debate

Lin, D., Shen, G., Yang, Z., Liu, T., Zhao, D., & Zeng, Y. (2025) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 8

Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models

Yi, J., Xie, Y., Zhu, B., Kiciman, E., Sun, G., Xie, X., & Wu, F. (2023) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 8

ChatLogic: Integrating Logic Programming with Large Language Models for Multi-Step Reasoning

Wang, Z., Liu, J., Bao, Q., Rong, H., & Zhang, J. (2024) · 2024 International Joint Conference on Neural Networks (IJCNN)

Logic, Reasoning, and KnowledgeAI-based Problem Solving and Planning

Cited by 8

A dataset for microscopic peripheral blood cell images for development of automatic recognition systems

Acevedo, A. (2020) · Mendeley

Digital Imaging for Blood DiseasesCell Image Analysis Techniques

Cited by 8