Check computer science papers: citations, claims and retractions

Generating Manga from Illustrations via Mimicking Manga Creation Workflow

Zhang, L., Wang, X., Fan, Q., Ji, Y., & Liu, C. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisComputer Graphics and Visualization Techniques

Cited by 20

Utilizing Learning Analytics to Map Students' Self-Reported Study Strategies to Click Behaviors in STEM Courses

Rodriguez, F., Yu, R., Park, J., Rivas, M. J., Warschauer, M., & Sato, B. K. (2019) · Proceedings of the 9th International Conference on Learning Analytics & Knowledge

Online Learning and AnalyticsInnovations in Educational Methods

Cited by 20

What's the Game, then? Opportunities and Challenges for Runtime Behavior Generation

Jennings, N., Wang, H., Li, I., Smith, J., & Hartmann, B. (2024) · Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology

Artificial Intelligence in GamesDigital Games and Media

Cited by 20

Is My Data in Your Retrieval Database? Membership Inference Attacks Against Retrieval Augmented Generation

Anderson, M., Amit, G., & Goldsteen, A. (2025) · Proceedings of the 11th International Conference on Information Systems Security and Privacy

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 20

Estimating Franck-Condon factors using an NMR quantum processor

Joshi, S., Shukla, A., Katiyar, H., Hazra, A., & Mahesh, T. S. (2014) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 20

Motion-Aware Correlation Filters for Online Visual Tracking

Zhang, Y., Yang, Y., Zhou, W., Shi, L., & Li, D. (2018) · Sensors

Video Surveillance and Tracking MethodsAdvanced Image and Video Retrieval Techniques

Cited by 20

Advanced Architectures Integrated With Agentic AI for Next-Generation Wireless Networks

Dev, K., Khowaja, S. A., Zeydan, E., Singh, K., & Debbah, M. (2025) · IEEE Communications Standards Magazine

Software-Defined Networks and 5GAdvanced Data and IoT Technologies

Cited by 20

Towards employing FPGA and ASIP acceleration to enable onboard AI/ML in space applications

Leon, V., Lentaris, G., Soudris, D., Vellas, S., & Bernou, M. (2022) · 2022 IFIP/IEEE 30th International Conference on Very Large Scale Integration (VLSI-SoC)

Embedded Systems Design TechniquesSpace Technology and Applications

Cited by 20

Improving the Energy Efficiency of Real-time DNN Object Detection via Compression, Transfer Learning, and Scale Prediction

Biswas, D., Rahman, M. M. M., Zong, Z., & Tesic, J. (2022) · 2022 IEEE International Conference on Networking, Architecture and Storage (NAS)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 20

A New Method to Measure Cortical Growth in the Developing Brain

Knutsen, A. K., Chang, Y. V., Grimm, C. M., Phan, L., Taber, L. A., & Bayly, P. V. (2010) · Journal of Biomechanical Engineering

Medical Image Segmentation TechniquesElasticity and Material Modeling

Cited by 20

BlockchainBus: A lightweight framework for secure virtual machine migration in cloud federations using blockchain

Doyle, J., Golec, M., & Gill, S. S. (2022) · SECURITY AND PRIVACY

Blockchain Technology Applications and SecurityCloud Computing and Resource Management

Cited by 20

Harnessing Digital Twin Security Simulations for systematic Cyber Threat Intelligence

Dietz, M., Schlette, D., & Pernul, G. (2022) · 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)

Information and Cyber SecurityNetwork Security and Intrusion Detection

Cited by 20

Hierarchical memories: Simulating quantum LDPC codes with local gates

Pattison, C. A., Krishna, A., & Preskill, J. (2023) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 20

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning

Seo, Y., Lee, K., Clavera, I., Kurutach, T., Shin, J., & Abbeel, P. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 20

Explainable differential diagnosis with dual-inference large language models

Zhou, S., Lin, M., Ding, S., Wang, J., Chen, C., Melton, G. B., Zou, J., & Zhang, R. (2025) · npj Health Systems

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 20

Efficient (Soft) Q-Learning for Text Generation with Limited Good Data

Guo, H., Tan, B., Liu, Z., Xing, E. P., & Hu, Z. (2021) · arXiv

Topic ModelingReinforcement Learning in Robotics

Cited by 20

Eye Tracking Metrics in Software Engineering

Hauser, F., Mottok, J., & Gruber, H. (2018) · Proceedings of the 3rd European Conference of Software Engineering Education

Gaze Tracking and Assistive TechnologySoftware Engineering Techniques and Practices

Cited by 20

Sketch2Code: Transformation of Sketches to UI in Real-time Using Deep Neural Network

Jain, V., Agrawal, P., Banga, S., Kapoor, R., & Gulyani, S. (2019) · arXiv

Usability and User Interface DesignSoftware Engineering Research

Cited by 20

COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations

Favory, X., Drossos, K., Virtanen, T., & Serra, X. (2020) · arXiv

Music and Audio ProcessingSpeech Recognition and Synthesis

Cited by 20

Cross-Language Transfer Learning, Continuous Learning, and Domain Adaptation for End-to-End Automatic Speech Recognition

Huang, J., Kuchaiev, O., O'Neill, P., Lavrukhin, V., Li, J., Flores, A., Kucsko, G., & Ginsburg, B. (2020) · arXiv

Speech Recognition and SynthesisDomain Adaptation and Few-Shot Learning

Cited by 20

AttendNets: Tiny Deep Image Recognition Neural Networks for the Edge via Visual Attention Condensers

Wong, A., Famouri, M., & Shafiee, M. J. (2020) · arXiv

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 20

Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards

Ramé, A., Couairon, G., Shukor, M., Dancette, C., Gaya, J.-B., Soulier, L., & Cord, M. (2023) · arXiv

Topic ModelingReinforcement Learning in Robotics

Cited by 20

How Much Does AI Impact Development Speed? an Enterprise-Based Randomized Controlled Trial

Paradis, E., Grey, K., Madison, Q., Nam, D., Macvean, A., Meimand, V., Zhang, N., Ferrari-Church, B., & Chandra, S. (2025) · 2025 IEEE/ACM 47th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 20

LiveBench: A Challenging, Contamination-Limited LLM Benchmark

White, C., Dooley, S., Roberts, M., Pal, A., Feuer, B., Jain, S., Shwartz-Ziv, R., Jain, N., Saifullah, K., Dey, S., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 20