Check computer science papers: citations, claims and retractions

A Deep Multi-Modal Explanation Model for Zero-Shot Learning

Liu, Y., & Tuytelaars, T. (2020) · IEEE Transactions on Image Processing

Explainable Artificial Intelligence (XAI)Domain Adaptation and Few-Shot Learning

Cited by 31

The learning analytics readiness instrument

Oster, M., Lonn, S., Pistilli, M. D., & Brown, M. G. (2016) · Proceedings of the Sixth International Conference on Learning Analytics & Knowledge - LAK '16

Online Learning and AnalyticsBig Data and Business Intelligence

Cited by 31

Towards eXplainable Artificial Intelligence (XAI) in Tax Law: The Need for a Minimum Legal Standard

Kuźniacki, B., Almada, M., Tyliński, K., Górski, L., Winogradska, B., & Zeldenrust, R. (2022) · World Tax Journal

Explainable Artificial Intelligence (XAI)Digitalization, Law, and Regulation

Cited by 31

Implicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data

Dueñas, H. R., Seah, C., Johnson, J. S., & Huckins, L. M. (2020) · Human Molecular Genetics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 31

Boosting Multimodal Large Language Models with Visual Tokens Withdrawal for Rapid Inference

Lin, Z., Lin, M., Lin, L., & Ji, R. (2024) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 31

DIAM: towards a model for describing appropriation processes through the evolution of digital artifacts

Belin, A., & Prié, Y. (2012) · Proceedings of the Designing Interactive Systems Conference

Innovative Human-Technology InteractionInformation Systems Theories and Implementation

Cited by 31

Metalearned Neural Memory

Munkhdalai, T., Sordoni, A., Wang, T., & Trischler, A. (2019) · arXiv

Domain Adaptation and Few-Shot LearningNeural Networks and Applications

Cited by 31

Machine Learning for Internet of Things-Based Smart Transportation Networks

Khawar, H., Soomro, T. R., & Kamal, M. A. (2022) · Advances in Human and Social Aspects of Technology

Internet of Things and AIRoad Transport and Highway Systems

Cited by 31

A Survey on LLM-powered Agents for Recommender Systems

Peng, Q., Liu, H., Huang, H., Yang, J., Yang, Q., & Shao, M. (2025) · Findings of the Association for Computational Linguistics: EMNLP 2025

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 31

AdaPlanner: Adaptive Planning from Feedback with Language Models

Sun, H., Zhuang, Y., Kong, L., Dai, B., & Zhang, C. (2023) · arXiv

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 31

Extracting Latent Steering Vectors from Pretrained Language Models

Subramani, N., Suresh, N., & Peters, M. E. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 31

Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives

Seger, E., Dreksler, N., Moulange, R., Dardaman, E., Schuett, J., Wei, K., Winter, C., Arnold, M., Ó hÉigeartaigh, S., Korinek, A., et al. (2023) · SSRN Electronic Journal

Ethics and Social Impacts of AILaw, AI, and Intellectual Property

Cited by 31

Using ChatGPT with Novice Arduino Programmers: Effects on Performance, Interest, Self-Efficacy, and Programming Ability

Johnson, D. M., Doss, W., & Estepp, C. M. (2024) · Journal of Research in Technical Careers

Teaching and Learning ProgrammingArduino and IoT Applications

Cited by 31

Embedding Societal Values into Social Media Algorithms

Bernstein, M., Christin, A., Hancock, J., Hashimoto, T., Jia, C., Lam, M., Meister, N., Persily, N., Piccardi, T., Saveski, M., et al. (2023) · Journal of Online Trust and Safety

Ethics and Social Impacts of AIMisinformation and Its Impacts

Cited by 31

Large Language Models Can be Lazy Learners: Analyze Shortcuts in In-Context Learning

Tang, R., Kong, D., Huang, L., & Xue, H. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 31

An experiment with the use of chatgpt for lcsh subject assignment on electronic theses and dissertations

Chow, E. H. C., Kao, T. J., & Li, X. (2024) · Cataloging & Classification Quarterly

Library Science and Information SystemsTopic Modeling

Cited by 31

Adaptive Debanding Filter

Tu, Z., Lin, J., Wang, Y., Adsumilli, B., & Bovik, A. C. (2020) · IEEE Signal Processing Letters

Image Enhancement TechniquesAdvanced Image Processing Techniques

Cited by 31

Aero: Automotive ethernet real-time observer for anomaly detection in in-vehicle networks

Jeong, S., Kim, H. K., Han, M. L., & Kwak, B. I. (2024) · IEEE Transactions on Industrial Informatics

Network Security and Intrusion DetectionArtificial Immune Systems Applications

Cited by 31

Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation?

Millidge, B., Salvatori, T., Song, Y., Bogacz, R., & Lukasiewicz, T. (2022) · arXiv

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 31

Beyond the Chat: Executable and Verifiable Text-Editing with LLMs

Laban, P., Vig, J., Hearst, M., Xiong, C., & Wu, C.-S. (2024) · Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology

Usability and User Interface DesignSoftware Engineering Research

Cited by 31

Secure Video Surveillance Framework in Smart City

Li, H., Xiezhang, T., Yang, C., Deng, L., & Yi, P. (2021) · Sensors

Cryptography and Data SecurityAdvanced Authentication Protocols Security

Cited by 31

Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction

Cauchois, M., Gupta, S., & Duchi, J. (2020) · arXiv

Machine Learning and AlgorithmsMachine Learning and Data Classification

Cited by 31

Automated detection and quantification of brain metastases on clinical MRI data using artificial neural networks

Pflüger, I., Wald, T., Isensee, F., Schell, M., Meredig, H., Schlamp, K., Bernhardt, D., Brugnara, G., Heußel, C. P., Debus, J., et al. (2022) · Neuro-Oncology Advances

Brain Tumor Detection and ClassificationBrain Metastases and Treatment

Cited by 31

Why Don’t You Do It Right? Analysing Annotators’ Disagreement in Subjective Tasks

Sandri, M., Leonardelli, E., Tonelli, S., & Jezek, E. (2023) · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion Mining

Cited by 31