Check computer science papers: citations, claims and retractions

A systematic review of explainable artificial intelligence in urban building energy modeling: methods, applications, and future directions

Darvishvand, L., Kamkari, B., Huang, M. J., & Hewitt, N. J. (2025) · Sustainable Cities and Society

Explainable Artificial Intelligence (XAI)Building Energy and Comfort Optimization

Cited by 42

Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias

Wolfe, R., Yang, Y., Howe, B., & Caliskan, A. (2023) · 2023 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIMultimodal Machine Learning Applications

Cited by 42

Using Targeted Feedback to Address Common Student Misconceptions in Introductory Programming: A Data-Driven Approach

Qian, Y., & Lehman, J. D. (2019) · Sage Open

Teaching and Learning ProgrammingStudent Assessment and Feedback

Cited by 42

Exploring expanding expertise: Artificial intelligence as an existential threat and the role of prestigious commentators, 2014–2018

Galanos, V. (2019) · Technology Analysis & Strategic Management

Ethics and Social Impacts of AIRisk Perception and Management

Cited by 42

Abductive Knowledge Induction from Raw Data

Dai, W.-Z., & Muggleton, S. (2021) · Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence

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

Cited by 42

Chain-of-Verification Reduces Hallucination in Large Language Models

Dhuliawala, S., Komeili, M., Xu, J., Raileanu, R., Li, X., Celikyilmaz, A., & Weston, J. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 42

Cultural Incongruencies in Artificial Intelligence

Prabhakaran, V., Qadri, R., & Hutchinson, B. (2022) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 42

Exploration on Integrating Accessibility into an AI Course

Tseng, C.-E., Jung, S. H., Elglaly, Y. N., Liu, Y., & Ludi, S. (2022) · Proceedings of the 53rd ACM Technical Symposium on Computer Science Education

Teaching and Learning ProgrammingDigital Accessibility for Disabilities

Cited by 42

ReCode: Robustness Evaluation of Code Generation Models

Wang, S., Li, Z., Qian, H., Yang, C., Wang, Z., Shang, M., Kumar, V., Tan, S., Ray, B., Bhatia, P., et al. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Software Engineering ResearchTopic Modeling

Cited by 42

Unlocking the Potential of AI/ML in DevSecOps: Effective Strategies and Optimal Practices

Camacho, N. G. (2024) · Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023

Software Engineering Techniques and PracticesSoftware System Performance and Reliability

Cited by 42

UMMAFormer: A Universal Multimodal-adaptive Transformer Framework for Temporal Forgery Localization

Zhang, R., Wang, H., Du, M., Liu, H., Zhou, Y., & Zeng, Q. (2023) · Proceedings of the 31st ACM International Conference on Multimedia

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 42

Evaluating large language models for software testing

Li, Y., Liu, P., Wang, H., Chu, J., & Wong, W. E. (2025) · Computer Standards & Interfaces

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 42

FEATURETranscending disciplinary boundaries in interaction design

Blevis, E., & Stolterman, E. (2009) · Interactions

Innovative Human-Technology InteractionInterdisciplinary Research and Collaboration

Cited by 42

Towards visual ego-motion learning in robots

Pillai, S., & Leonard, J. J. (2017) · 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 42

Federated learning architecture: Design, implementation, and challenges in distributed AI systems

Shanmugam, L., Tillu, R., & Tomar, M. (2023) · Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online)

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 42

The evolved radio and its implications for modelling the evolution of novel sensors

Bird, J., & Layzell, P. (2003) · Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)

Evolutionary Algorithms and ApplicationsModular Robots and Swarm Intelligence

Cited by 42

Just What do You Think You're Doing, Dave?' A Checklist for Responsible Data Use in NLP

Rogers, A., Baldwin, T., & Leins, K. (2021) · arXiv

Ethics and Social Impacts of AIResearch Data Management Practices

Cited by 42

Predicting Design Impactful Changes in Modern Code Review: A Large-Scale Empirical Study

Uchoa, A., Barbosa, C., Coutinho, D., Oizumi, W., Assuncao, W. K. G., Vergilio, S. R., Pereira, J. A., Oliveira, A., & Garcia, A. (2021) · 2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR)

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 42

A STRATEGIC METAGAME PLAYER FOR GENERAL CHESS‐LIKE GAMES

Pell, B. (1996) · Computational Intelligence

Artificial Intelligence in GamesAI-based Problem Solving and Planning

Cited by 42

A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Ranjan, R., Gupta, S., & Singh, S. N. (2024) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 42

Metaphors in Voice User Interfaces: A Slippery Fish

Desai, S., & Twidale, M. (2023) · ACM Transactions on Computer-Human Interaction

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 42

A Comprehensive Network Security Risk Model for Process Control Networks

Henry, M. H., & Haimes, Y. Y. (2009) · Risk Analysis

Information and Cyber SecuritySmart Grid Security and Resilience

Cited by 42

Faster, deeper, easier: crowdsourcing diagnosis of microservice kernel failure from user space

Pan, Y., Ma, M., Jiang, X., & Wang, P. (2021) · Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 42

Calibrating ensembles for scalable uncertainty quantification in deep learning-based medical image segmentation

Buddenkotte, T., Escudero Sanchez, L., Crispin-Ortuzar, M., Woitek, R., McCague, C., Brenton, J. D., Öktem, O., Sala, E., & Rundo, L. (2023) · Computers in Biology and Medicine

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 42