Check computer science papers: citations, claims and retractions

Evaluating how developers use general-purpose web-search for code retrieval

Rahman, M. M., Barson, J., Paul, S., Kayani, J., Lois, F. A., Quezada, S. F., Parnin, C., Stolee, K. T., & Ray, B. (2018) · Proceedings of the 15th International Conference on Mining Software Repositories

Software Engineering ResearchInformation Retrieval and Search Behavior

Cited by 62

Bayesian Characterization of Uncertainty in Intra-subject Non-rigid Registration

Risholm, P., Janoos, F., Norton, I., Golby, A. J., & Wells, W. M. (2013) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Radiotherapy Techniques

Cited by 62

AI-Driven Development Is Here: Should You Worry?

Ernst, N. A., & Bavota, G. (2022) · IEEE Software

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 62

LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism

Wu, B., Liu, S., Zhong, Y., Sun, P., Liu, X., & Jin, X. (2024) · Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles

Parallel Computing and Optimization TechniquesNatural Language Processing Techniques

Cited by 62

Zero trust: Never trust, always verify

Wylde, A. (2021) · 2021 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)

Information and Cyber SecurityAccess Control and Trust

Cited by 62

Network configuration synthesis with abstract topologies

Beckett, R., Mahajan, R., Millstein, T., Padhye, J., & Walker, D. (2017) · Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation

Software-Defined Networks and 5GNetwork Traffic and Congestion Control

Cited by 62

Ethical Challenges for Learning Analytics

Ferguson, R. (2019) · Journal of Learning Analytics

Online Learning and AnalyticsDigital Education and Society

Cited by 62

Modeling and simulation of oscillator-based random number generators

Petrie, C. S., & Connelly, J. A. (1996) · 1996 IEEE International Symposium on Circuits and Systems (ISCAS)

Physical Unclonable Functions (PUFs) and Hardware SecurityLow-power high-performance VLSI design

Cited by 62

When people and algorithms meet: user-reported problems in intelligent everyday applications

Eiband, M., Völkel, S. T., Buschek, D., Cook, S., & Hussmann, H. (2019) · Proceedings of the 24th International Conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)Innovative Human-Technology Interaction

Cited by 62

Leakage-Adjusted Simulatability: Can Models Generate Non-Trivial Explanations of Their Behavior in Natural Language?

Hase, P., Zhang, S., Xie, H., & Bansal, M. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 62

Widening Access to Applied Machine Learning with TinyML

Janapa Reddi, V., Plancher, B., Kennedy, S., Moroney, L., Warden, P., Suzuki, L., Agarwal, A., Banbury, C., Banzi, M., Bennett, M., et al. (2022) · Harvard Data Science Review

Online Learning and AnalyticsTeaching and Learning Programming

Cited by 62

Optimization Applications as Quantum Performance Benchmarks

Lubinski, T., Coffrin, C., McGeoch, C., Sathe, P., Apanavicius, J., & Neira, D. E. B. (2023) · arXiv

Quantum Computing Algorithms and ArchitectureMetaheuristic Optimization Algorithms Research

Cited by 62

End-to-End Slicing as a Service with Computing and Communication Resource Allocation for Multi-Tenant 5G Systems

Chien, H.-T., Lin, Y.-D., Lai, C.-L., & Wang, C.-T. (2019) · IEEE Wireless Communications

Software-Defined Networks and 5GIoT and Edge/Fog Computing

Cited by 62

SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Model

Huang, Z., Hu, J., Li, X., He, Y., Zhao, X., Peng, B., Wu, B., Huang, X., & Cheng, G. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 62

Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering

Wang, R., Guo, J., Gao, C., Fan, G., Chong, C. Y., & Xia, X. (2025) · Proceedings of the ACM on Software Engineering

Software Engineering ResearchTopic Modeling

Cited by 62

The Automatic Detection of Speech Disorders in Children: Challenges, Opportunities, and Preliminary Results

Shahin, M., Zafar, U., & Ahmed, B. (2020) · IEEE Journal of Selected Topics in Signal Processing

Speech Recognition and SynthesisLanguage Development and Disorders

Cited by 62

Deep learning ensemble approach with explainable AI for lung and colon cancer classification using advanced hyperparameter tuning

Vanitha, K., R, M. T., Sree, S. S., & Guluwadi, S. (2024) · BMC Medical Informatics and Decision Making

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 62

Incremental-DETR: Incremental Few-Shot Object Detection via Self-Supervised Learning

Dong, N., Zhang, Y., Ding, M., & Lee, G. H. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 62

XNAT Central: Open sourcing imaging research data

Herrick, R., Horton, W., Olsen, T., McKay, M., Archie, K. A., & Marcus, D. S. (2016) · NeuroImage

Research Data Management PracticesData Analysis and Archiving

Cited by 62

Sibyl: Understanding and addressing the usability challenges of machine learning in high-stakes decision making

Zytek, A., Liu, D., Vaithianathan, R., & Veeramachaneni, K. (2022) · IEEE Transactions on Visualization and Computer Graphics

Explainable Artificial Intelligence (XAI)Data Visualization and Analytics

Cited by 62

DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions

Ghosal, T., Verma, R., Ekbal, A., & Bhattacharyya, P. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Sentiment Analysis and Opinion MiningRecommender Systems and Techniques

Cited by 62

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

Fahim, F., Hawks, B., Herwig, C., Hirschauer, J., Jindariani, S., Tran, N., Carloni, L. P., Di Guglielmo, G., Harris, P., Krupa, J., et al. (2021) · arXiv

Embedded Systems Design TechniquesAdvanced Neural Network Applications

Cited by 62

Do We Still Need Clinical Language Models?

Lehman, E., Hernandez, E., Mahajan, D., Wulff, J., Smith, M. J., Ziegler, Z., Nadler, D., Szolovits, P., Johnson, A., & Alsentzer, E. (2023) · arXiv

Machine Learning in HealthcareTopic Modeling

Cited by 62

Cognitive bias in decision-making with LLMs

Echterhoff, J. M., Liu, Y., Alessa, A., McAuley, J., & He, Z. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 62