Check computer science papers: citations, claims and retractions

Causal Deep Learning

Berrevoets, J., Kacprzyk, K., Qian, Z., & van der Schaar, M. (2023) · arXiv

Bayesian Modeling and Causal InferenceAdvanced Causal Inference Techniques

Cited by 8

The Role of Blockchain in Supporting Critical National Infrastructure

Kendzierskyj, S., & Jahankhani, H. (2019) · 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)

Blockchain Technology Applications and SecurityInformation and Cyber Security

Cited by 8

Effective Prompt Extraction from Language Models

Zhang, Y., Carlini, N., & Ippolito, D. (2023) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 8

Wish I hadn't clicked that: context based icons for mobile web navigation and directed search tasks

Setlur, V., Rossoff, S., & Gooch, B. (2011) · Proceedings of the 16th international conference on Intelligent user interfaces

Data Visualization and AnalyticsInformation Retrieval and Search Behavior

Cited by 8

Transversal Clifford and T -Gate Codes of Short Length and High Distance

Jain, S. P., & Albert, V. V. (2025) · IEEE Journal on Selected Areas in Information Theory

Quantum Computing Algorithms and ArchitectureCoding theory and cryptography

Cited by 8

A Vision of the Future: Harnessing Artificial Intelligence for Strategic Social Marketing

Evans, W. D., Bardus, M., & French, J. (2024) · Businesses

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 8

How can ontologies give you clue for truth-discovery? an exploratory study

Beretta, V., Harispe, S., Ranwez, S., & Mougenot, I. (2016) · Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics

Semantic Web and OntologiesMobile Crowdsensing and Crowdsourcing

Cited by 8

Multi-Agent Security Tax: Trading Off Security and Collaboration Capabilities in Multi-Agent Systems

Peigné, P., Kniejski, M., Sondej, F., David, M., Hoelscher-Obermaier, J., Schroeder de Witt, C., & Kran, E. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence

Adversarial Robustness in Machine LearningAccess Control and Trust

Cited by 8

GAR-meets-RAG Paradigm for Zero-Shot Information Retrieval

Arora, D., Kini, A., Chowdhury, S. R., Natarajan, N., Sinha, G., & Sharma, A. (2023) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 8

Improving vehicle tracking rate and speed estimation in dusty and snowy weather conditions with a vibrating camera

Yaghoobi Ershadi, N. (2017) · PLOS ONE

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 8

Detecting Quishing Attacks with Machine Learning Techniques Through QR Code Analysis

Trad, F., & Chehab, A. (2027) · IFIP Advances in Information and Communication Technology

Spam and Phishing DetectionUser Authentication and Security Systems

Cited by 8

LLM-Powered Code Vulnerability Repair with Reinforcement Learning and Semantic Reward

Islam, N. T., Khoury, J., Seong, A., Karkevandi, M. B., Parra, G. D. L. T., Bou-Harb, E., & Najafirad, P. (2024) · arXiv

Software Engineering ResearchWeb Application Security Vulnerabilities

Cited by 8

Transition-Aware Detection of Modes of Locomotion and Transportation Through Hierarchical Segmentation

Akbari, A., & Jafari, R. (2021) · IEEE Sensors Journal

Context-Aware Activity Recognition SystemsHuman Mobility and Location-Based Analysis

Cited by 8

Bogazici mouse dynamics dataset

Kılıç, A. A., Yıldırım, M., & Anarım, E. (2021) · Data in Brief

User Authentication and Security SystemsNetwork Security and Intrusion Detection

Cited by 8

Auxiliary task demands mask the capabilities of smaller language models

Hu, J., & Frank, M. C. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 8

FaithBench: A Diverse Hallucination Benchmark for Summarization by Modern LLMs

Bao, F. S., Li, M., Qu, R., Luo, G., Wan, E., Tang, Y., Fan, W., Tamber, M. S., Kazi, S., Sourabh, V., et al. (2025) · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 8

Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement

Ye, H., Jin, J., Xie, Y., Zhang, X., & Song, G. (2025) · arXiv

Topic ModelingEthics and Social Impacts of AI

Cited by 8

Usability evaluation of academic library websites: a systematic literature review

Jilani, M. A., Sheikh, A., Shah, F. A., & Saqlain, S. M. (2026) · Information Discovery and Delivery

Usability and User Interface DesignWeb and Library Services

Cited by 8

An intelligent, two-stage, in-vehicle diagnostic-based secured framework

Awaad, T. A., El-Kharashi, M. W., Taher, M., & Ammar, K. A. (2022) · IEEE Access

Network Security and Intrusion DetectionAdversarial Robustness in Machine Learning

Cited by 8

SpiderMesh: Spatial-aware demand-guided recursive meshing for RGB-T semantic segmentation

Fan, S., Wang, Z., Wang, Y., & Liu, J. (2023) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 8

GPT-4 as an Effective Zero-Shot Evaluator for Scientific Figure Captions

Hsu, T.-Y., Huang, C.-Y., Rossi, R., Kim, S., Giles, C. L., & Huang, T.-H. K. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 8

Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices

Wu, C. P., Shirley, R. B., Milinovich, A., Liu, K., Mireles-Cabodevila, E., Khouli, H., Duggal, A., & Bhattacharyya, A. (2025) · Intensive Care Medicine Experimental

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 8

Effects of asymmetry between design models and user models on subjective comprehension of user interface

Doi, T. (2021) · Symmetry

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 8

Multimodal Generative Models for Compositional Representation Learning

Wu, M., & Goodman, N. (2019) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 8