Check computer science papers: citations, claims and retractions

Decoupling Representation Learning from Reinforcement Learning

Stooke, A., Lee, K., Abbeel, P., & Laskin, M. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 123

Accelerating Deep Convolutional Networks using low-precision and sparsity

Venkatesh, G., Nurvitadhi, E., & Marr, D. (2017) · 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 123

Devising and Detecting Phishing Emails Using Large Language Models

Heiding, F., Schneier, B., Vishwanath, A., Bernstein, J., & Park, P. S. (2024) · IEEE Access

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 123

A sustainable incentive scheme for federated learning

Yu, H., Liu, Z., Liu, Y., Chen, T., Cong, M., Weng, X., Niyato, D., & Yang, Q. (2020) · IEEE Intelligent Systems

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 123

Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

Xu, H., Sharaf, A., Chen, Y., Tan, W., Shen, L., Van Durme, B., Murray, K., & Kim, Y. J. (2024) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 123

Analyzing Activity Behavior and Movement in a Naturalistic Environment Using Smart Home Techniques

Cook, D. J., Schmitter-Edgecombe, M., & Dawadi, P. (2015) · IEEE Journal of Biomedical and Health Informatics

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 123

Fact-free learning

Aragones, E., Gilboa, I., Postlewaite, A., & Schmeidler, D. (2005) · American Economic Review

Bayesian Modeling and Causal InferenceMachine Learning and Algorithms

Cited by 123

Just ask for calibration: Strategies for eliciting calibrated confidence scores from language models fine-tuned with human feedback

Tian, K., Mitchell, E., Zhou, A., Sharma, A., Rafailov, R., Yao, H., Finn, C., & Manning, C. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 123

Finding missed cases of familial hypercholesterolemia in health systems using machine learning

Banda, J. M., Sarraju, A., Abbasi, F., Parizo, J., Pariani, M., Ison, H., Briskin, E., Wand, H., Dubois, S., Jung, K., et al. (2019) · npj Digital Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 123

The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships

Zhang, R., Li, H., Meng, H., Zhan, J., Gan, H., & Lee, Y.-C. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AISocial Robot Interaction and HRI

Cited by 123

Case Base Querying for Travel Planning Recommendation

Ricci, F., & Werthner, H. (2001) · Information Technology & Tourism

Recommender Systems and TechniquesAI-based Problem Solving and Planning

Cited by 123

Dynamic programming and a new formalism in the calculus of variations

Bellman, R. (1954) · Proceedings of the National Academy of Sciences

Optimization and Variational AnalysisOptimization and Mathematical Programming

Cited by 123

The Who in XAI: How AI Background Shapes Perceptions of AI Explanations

Ehsan, U., Passi, S., Liao, Q. V., Chan, L., Lee, I.-H., Muller, M., & Riedl, M. O. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 123

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer

Zhou, D., Tian, F., Tian, X., Sun, L., Huang, X., Zhao, F., Zhou, N., Chen, Z., Zhang, Q., Yang, M., et al. (2020) · Nature Communications

AI in cancer detectionColorectal Cancer Screening and Detection

Cited by 123

AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-Decoder

Lee, Y., & Kang, P. (2022) · arXiv

Anomaly Detection Techniques and ApplicationsIndustrial Vision Systems and Defect Detection

Cited by 123

Who Are You? A Statistical Approach to Measuring User Authenticity

Freeman, D., Jain, S., Duermuth, M., Biggio, B., & Giacinto, G. (2016) · Proceedings 2016 Network and Distributed System Security Symposium

User Authentication and Security SystemsSpam and Phishing Detection

Cited by 123

Active learning for biomedical citation screening

Wallace, B. C., Small, K., Brodley, C. E., & Trikalinos, T. A. (2010) · Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining

Machine Learning and AlgorithmsMeta-analysis and systematic reviews

Cited by 123

Privacy-preserving Federated Deep Learning for Wearable IoT-based Biomedical Monitoring

Can, Y. S., & Ersoy, C. (2021) · ACM Transactions on Internet Technology

Privacy-Preserving Technologies in DataEmotion and Mood Recognition

Cited by 123

“Learning latent engagement patterns of students in online courses,”

Ramesh, A., Goldwasser, D., Huang, B., Daume III, H., & Getoor, L. (2014) · Proceedings of the AAAI Conference on Artificial Intelligence

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 123

Unsupervised Question Decomposition for Question Answering

Perez, E., Lewis, P., Yih, W.-T., Cho, K., & Kiela, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 123

Multi-relational Poincaré Graph Embeddings

Balažević, I., Allen, C., & Hospedales, T. (2019) · arXiv

Advanced Graph Neural NetworksTopic Modeling

Cited by 123

On a Novel Deep-Learning-Based Intelligent Partially Overlapping Channel Assignment in SDN-IoT

Tang, F., Mao, B., Fadlullah, Z. M., & Kato, N. (2018) · IEEE Communications Magazine

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

Cited by 123

From Data to Insights: A Layered Storytelling Approach for Multimodal Learning Analytics

Martinez-Maldonado, R., Echeverria, V., Fernandez Nieto, G., & Buckingham Shum, S. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Online Learning and AnalyticsData Visualization and Analytics

Cited by 123

Artificial intelligence in support of the circular economy: ethical considerations and a path forward

Roberts, H., Zhang, J., Bariach, B., Cowls, J., Gilburt, B., Juneja, P., Tsamados, A., Ziosi, M., Taddeo, M., & Floridi, L. (2024) · AI & SOCIETY

Ethics and Social Impacts of AISustainable Supply Chain Management

Cited by 123