Check computer science papers: citations, claims and retractions

An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation

Tufano, M., Watson, C., Bavota, G., Penta, M. D., White, M., & Poshyvanyk, D. (2019) · ACM Transactions on Software Engineering and Methodology

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 370

Factorizing YAGO: scalable machine learning for linked data

Nickel, M., Tresp, V., & Kriegel, H.-P. (2012) · Proceedings of the 21st international conference on World Wide Web

Semantic Web and OntologiesAdvanced Graph Neural Networks

Cited by 370

In defense of color-based model-free tracking

Possegger, H., Mauthner, T., & Bischof, H. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 370

Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

Zhang, Q., Hu, C., Upasani, S., Ma, B., Hong, F., Kamanuru, V., Rainton, J., Wu, C., Ji, M., Li, H., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 370

A systematic literature review of automated feedback generation for programming exercises

Keuning, H., Jeuring, J., & Heeren, B. (2019) · ACM Transactions on Computing Education

Teaching and Learning ProgrammingStudent Assessment and Feedback

Cited by 370

Axial Attention in Multidimensional Transformers

Ho, J., Kalchbrenner, N., Weissenborn, D., & Salimans, T. (2019) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 370

Time Delay Estimation in Room Acoustic Environments: An Overview

Chen, J., Benesty, J., & Huang, Y. (2006) · EURASIP Journal on Advances in Signal Processing

Speech and Audio ProcessingDirection-of-Arrival Estimation Techniques

Cited by 370

Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning

Nagabandi, A., Clavera, I., Liu, S., Fearing, R. S., Abbeel, P., Levine, S., & Finn, C. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 370

An empirical analysis of journal policy effectiveness for computational reproducibility

Stodden, V., Seiler, J., & Ma, Z. (2018) · Proceedings of the National Academy of Sciences

Research Data Management PracticesScientific Computing and Data Management

Cited by 369

Algorithmic governance: Developing a research agenda through the power of collective intelligence

Danaher, J., Hogan, M. J., Noone, C., Kennedy, R., Behan, A., De Paor, A., Felzmann, H., Haklay, M., Khoo, S.-M., Morison, J., et al. (2017) · Big Data & Society

Ethics and Social Impacts of AIE-Government and Public Services

Cited by 369

Dynamic Controller Provisioning in Software Defined Networks

Bari, M. F., Roy, A. R., Chowdhury, S. R., Zhang, Q., Zhani, M. F., Ahmed, R., & Boutaba, R. (2013) · Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013)

Software-Defined Networks and 5GAdvanced Optical Network Technologies

Cited by 369

AI and Memory Wall

Gholami, A., Yao, Z., Kim, S., Hooper, C., Mahoney, M. W., & Keutzer, K. (2024) · IEEE Micro

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 369

Can Generative AI improve social science?

Bail, C. A. (2024) · Proceedings of the National Academy of Sciences

Ethics and Social Impacts of AIComputational and Text Analysis Methods

Cited by 369

Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance

Dratsch, T., Chen, X., Rezazade Mehrizi, M., Kloeckner, R., Mähringer-Kunz, A., Püsken, M., Baeßler, B., Sauer, S., Maintz, D., & Pinto dos Santos, D. (2023) · Radiology

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 369

Associatron-A Model of Associative Memory

Nakano, K. (1972) · IEEE Transactions on Systems, Man, and Cybernetics

Neural Networks and ApplicationsCognitive Computing and Networks

Cited by 369

Can Generative AI Improve Social Science?

Bail, C. A. (2023) · Proceedings of the National Academy of Sciences

Ethics and Social Impacts of AIComputational and Text Analysis Methods

Cited by 369

On-body localization of wearable devices: An investigation of position-aware activity recognition

Sztyler, T., & Stuckenschmidt, H. (2016) · 2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)

Context-Aware Activity Recognition SystemsIndoor and Outdoor Localization Technologies

Cited by 369

The use of inertial sensors system for human motion analysis

Cuesta-Vargas, A. I., Galán-Mercant, A., & Williams, J. M. (2010) · Physical Therapy Reviews

Context-Aware Activity Recognition SystemsInertial Sensor and Navigation

Cited by 369

Cross-modal Memory Networks for Radiology Report Generation

Chen, Z., Shen, Y., Song, Y., & Wan, X. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 369

NeuFlow: A runtime reconfigurable dataflow processor for vision

Farabet, C., Martini, B., Corda, B., Akselrod, P., Culurciello, E., & LeCun, Y. (2011) · CVPR 2011 WORKSHOPS

Embedded Systems Design TechniquesAdvanced Neural Network Applications

Cited by 369

A Survey on Multimodal Large Language Models for Autonomous Driving

Cui, C., Ma, Y., Cao, X., Ye, W., Zhou, Y., Liang, K., Chen, J., Lu, J., Yang, Z., Liao, K.-D., et al. (2024) · 2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)

Multimodal Machine Learning ApplicationsAutonomous Vehicle Technology and Safety

Cited by 369

Twitter discussions and emotions about the COVID-19 pandemic: Machine learning approach

Xue, J., Chen, J., Hu, R., Chen, C., Zheng, C., Su, Y., & Zhu, T. (2020) · Journal of Medical Internet Research

Sentiment Analysis and Opinion MiningCommunication and COVID-19 Impact

Cited by 369

Apples-to-apples in cross-validation studies: pitfalls in classifier performance measurement

Forman, G., & Scholz, M. (2010) · ACM SIGKDD Explorations Newsletter

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 368

A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition

Chen, K., Yao, L., Zhang, D., Wang, X., Chang, X., & Nie, F. (2020) · IEEE Transactions on Neural Networks and Learning Systems

Context-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Cited by 368