Check computer science papers: citations, claims and retractions

MetaICL: Learning to Learn In Context

Min, S., Lewis, M., Zettlemoyer, L., & Hajishirzi, H. (2021) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 61

A Security- and Privacy-Preserving Approach Based on Data Disturbance for Collaborative Edge Computing in Social IoT Systems

Zhang, P., Wang, Y., Kumar, N., Jiang, C., & Shi, G. (2022) · IEEE Transactions on Computational Social Systems

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 61

A new iterative method to reduce workload in systematic review process

Jonnalagadda, S., & Petitti, D. (2013) · International Journal of Computational Biology and Drug Design

Information Retrieval and Search BehaviorMeta-analysis and systematic reviews

Cited by 61

Negotiating Women’s Agency through ICTs: A Comparative Study of Uganda and India

Masika, R., & Bailur, S. (2015) · Gender, Technology and Development

ICT in Developing CommunitiesGender and Technology in Education

Cited by 61

Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery

Wissel, B. D., Greiner, H. M., Glauser, T. A., Holland‐Bouley, K. D., Mangano, F. T., Santel, D., Faist, R., Zhang, N., Pestian, J. P., Szczesniak, R. D., et al. (2020) · Epilepsia

Machine Learning in HealthcareEpilepsy research and treatment

Cited by 61

Sparse Autoencoders Find Highly Interpretable Features in Language Models

Cunningham, H., Ewart, A., Riggs, L., Huben, R., & Sharkey, L. (2023) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 61

Fog-Embedded Deep Learning for the Internet of Things

Lyu, L., Bezdek, J. C., He, X., & Jin, J. (2019) · IEEE Transactions on Industrial Informatics

IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in Data

Cited by 61

OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations

Ouyang, L., Qu, Y., Zhou, H., Zhu, J., Zhang, R., Lin, Q., Wang, B., Zhao, Z., Jiang, M., Zhao, X., et al. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Handwritten Text Recognition TechniquesInformation Systems and Technology Applications

Cited by 61

Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime

Dai, D., & Van Gool, L. (2018) · ETH Zurich

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 60

Feature selection and classification of imbalanced datasets

Duchesnay, E., Cachia, A., Boddaert, N., Chabane, N., Mangin, J.-F., Martinot, J.-L., Brunelle, F., & Zilbovicius, M. (2011) · NeuroImage

Imbalanced Data Classification TechniquesAutism Spectrum Disorder Research

Cited by 60

Breaking out of the Lab: Mitigating Mind Wandering with Gaze-Based Attention-Aware Technology in Classrooms

Hutt, S., Krasich, K., R. Brockmole, J., & K. D'Mello, S. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Intelligent Tutoring Systems and Adaptive LearningMind wandering and attention

Cited by 60

Deep semantic classification for 3D LiDAR data

Dewan, A., Oliveira, G. L., & Burgard, W. (2017) · 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robotics and Sensor-Based LocalizationAdvanced Neural Network Applications

Cited by 60

Agile requirements engineering with prototyping: A case study

Kapyaho, M., & Kauppinen, M. (2015) · 2015 IEEE 23rd International Requirements Engineering Conference (RE)

Software Engineering Techniques and PracticesAdvanced Software Engineering Methodologies

Cited by 60

Efficient Multimodal Fusion via Interactive Prompting

Li, Y., Quan, R., Zhu, L., & Yang, Y. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 60

Being Old Doesn’t Mean Acting Old: How Older Users Interact with Spoken Dialog Systems

Wolters, M., Georgila, K., Moore, J. D., & MacPherson, S. E. (2009) · ACM Transactions on Accessible Computing

Speech and dialogue systemsTechnology Use by Older Adults

Cited by 60

Free software/free science

Kelty, C. M. (2001) · First Monday

Open Source Software InnovationsAcademic Publishing and Open Access

Cited by 60

A Critical Reflection on Visualization Research: Where Do Decision Making Tasks Hide?

Dimara, E., & Stasko, J. (2022) · IEEE Transactions on Visualization and Computer Graphics

Data Visualization and AnalyticsDecision Support System Applications

Cited by 60

Memory-assisted prompt editing to improve GPT-3 after deployment

Madaan, A., Tandon, N., Clark, P., & Yang, Y. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 60

Same, Same But Different - Recovering Neural Network Quantization Error Through Weight Factorization

Meller, E., Finkelstein, A., Almog, U., & Grobman, M. (2019) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 60

Counterexample-Guided Data Augmentation

Dreossi, T., Ghosh, S., Yue, X., Keutzer, K., Sangiovanni-Vincentelli, A., & Seshia, S. A. (2018) · Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence

Adversarial Robustness in Machine LearningMachine Learning and Data Classification

Cited by 60

Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions

Lamaakal, I., Maleh, Y., El Makkaoui, K., Ouahbi, I., Pławiak, P., Alfarraj, O., Almousa, M., & Abd El-Latif, A. A. (2025) · Sensors

Advanced Neural Network ApplicationsTopic Modeling

Cited by 60

How Widely Can Prediction Models Be Generalized? Performance Prediction in Blended Courses

Gitinabard, N., Xu, Y., Heckman, S., Barnes, T., & Lynch, C. F. (2019) · IEEE Transactions on Learning Technologies

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 60

LM vs LM: Detecting Factual Errors via Cross Examination

Cohen, R., Hamri, M., Geva, M., & Globerson, A. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingMisinformation and Its Impacts

Cited by 60

Coreference Resolution without Span Representations

Kirstain, Y., Ram, O., & Levy, O. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 60