Check computer science papers: citations, claims and retractions

The Application of Blockchain Technology in the Field of Digital Forensics: A Literature Review

Igonor, O. S., Amin, M. B., & Garg, S. (2025) · Blockchains

Digital and Cyber ForensicsBlockchain Technology Applications and Security

Cited by 44

Using Colors to Detect Structural Components in Digital Pictures

Abeid Neto, J., Arditi, D., & Evens, M. W. (2002) · Computer-Aided Civil and Infrastructure Engineering

Image and Object Detection TechniquesInfrastructure Maintenance and Monitoring

Cited by 44

Assistance and Feedback Mechanism in an Intelligent Tutoring System for Teaching Conversion of Natural Language into Logic

Perikos, I., Grivokostopoulou, F., & Hatzilygeroudis, I. (2017) · International Journal of Artificial Intelligence in Education

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 44

Practical Evaluation of VMAF Perceptual Video Quality for WebRTC Applications

García, B., López-Fernández, L., Gortázar, F., & Gallego, M. (2019) · Electronics

Image and Video Quality AssessmentNetwork Traffic and Congestion Control

Cited by 44

CodeJudge: Evaluating Code Generation with Large Language Models

Tong, W., & Zhang, T. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 44

Towards an Analysis of Program Complexity From a Cognitive Perspective

Duran, R., Sorva, J., & Leite, S. (2018) · Proceedings of the 2018 ACM Conference on International Computing Education Research

Teaching and Learning ProgrammingVisual and Cognitive Learning Processes

Cited by 44

Remote Labor Index: Measuring AI Automation of Remote Work

Mazeika, M., Gatti, A., Menghini, C., Sehwag, U. M., Singhal, S., Orlovskiy, Y., Basart, S., Sharma, M., Peskoff, D., Lau, E., et al. (2025) · arXiv

Artificial Intelligence ApplicationsLabor market dynamics and wage inequality

Cited by 44

Behaviors of Higher and Lower Performing Students in CS1

Liao, S. N., Valstar, S., Thai, K., Alvarado, C., Zingaro, D., Griswold, W. G., & Porter, L. (2019) · Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education

Teaching and Learning ProgrammingOnline Learning and Analytics

Cited by 44

A Survey of Resource-efficient LLM and Multimodal Foundation Models

Xu, M., Yin, W., Cai, D., Yi, R., Xu, D., Wang, Q., Wu, B., Zhao, Y., Yang, C., Wang, S., et al. (2024) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 44

HMF: simple type inference for first-class polymorphism

Leijen, D. (2008) · Proceedings of the 13th ACM SIGPLAN international conference on Functional programming

Logic, programming, and type systemsSyntax, Semantics, Linguistic Variation

Cited by 44

Convolutional Neural Network with Median Layers for Denoising Salt-and-Pepper Contaminations

Liang, L., Deng, S., Gueguen, L., Wei, M., Wu, X., & Qin, J. (2019) · arXiv

Image and Signal Denoising MethodsImage Enhancement Techniques

Cited by 44

SNIPER: Few-shot Learning for Anomaly Detection to Minimize False-negative Rate with Ensured True-positive Rate

Koizumi, Y., Murata, S., Harada, N., Saito, S., & Uematsu, H. (2019) · ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Anomaly Detection Techniques and ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 44

TinyDL: Edge Computing and Deep Learning Based Real-time Hand Gesture Recognition Using Wearable Sensor

Coffen, B., & Mahmud, M. S. (2021) · 2020 IEEE International Conference on E-health Networking, Application & Services (HEALTHCOM)

Hand Gesture Recognition SystemsContext-Aware Activity Recognition Systems

Cited by 44

ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding

Guo, Z., Tang, Y., Zhang, R., Wang, D., Wang, Z., Zhao, B., & Li, X. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 44

Toward Usable Evidence: Optimizing Knowledge Accumulation in HCI Research on Health Behavior Change

Klasnja, P., Hekler, E. B., Korinek, E. V., Harlow, J., & Mishra, S. R. (2017) · Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionMobile Health and mHealth Applications

Cited by 44

Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy

Mireshghallah, F., Taram, M., Jalali, A., Elthakeb, A. T., Tullsen, D., & Esmaeilzadeh, H. (2020) · arXiv

Privacy-Preserving Technologies in DataCloud Data Security Solutions

Cited by 44

Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables

Varamin, A. A., Abbasnejad, E., Shi, Q., Ranasinghe, D. C., & Rezatofighi, H. (2018) · Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Context-Aware Activity Recognition SystemsTime Series Analysis and Forecasting

Cited by 44

Deductive Verification of Chain-of-Thought Reasoning

Ling, Z., Fang, Y., Li, X., Huang, Z., Lee, M., Memisevic, R., & Su, H. (2023) · Advances in Neural Information Processing Systems 36

Logic, Reasoning, and KnowledgeLogic, programming, and type systems

Cited by 44

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Suzgun, M., Scales, N., Schärli, N., Gehrmann, S., Tay, Y., Chung, H. W., Chowdhery, A., Le, Q. V., Chi, E. H., Zhou, D., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 44

Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling

Dinan, E., Abercrombie, G., Bergman, A. S., Spruit, S., Hovy, D., Boureau, Y.-L., & Rieser, V. (2021) · arXiv

Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection

Cited by 44

Explainable AI-based Federated Deep Reinforcement Learning for Trusted Autonomous Driving

Rjoub, G., Bentahar, J., & Wahab, O. A. (2022) · 2022 International Wireless Communications and Mobile Computing (IWCMC)

Privacy-Preserving Technologies in DataAutonomous Vehicle Technology and Safety

Cited by 44

Exploring Length Generalization in Large Language Models

Anil, C., Wu, Y., Andreassen, A., Lewkowycz, A., Misra, V., Ramasesh, V., Slone, A., Gur-Ari, G., Dyer, E., & Neyshabur, B. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 44

HCNN: Heterogeneous Convolutional Neural Networks for Comorbid Risk Prediction with Electronic Health Records

Zhang, J., Gong, J., & Barnes, L. (2017) · 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)

Machine Learning in HealthcareAdvanced Graph Neural Networks

Cited by 44

MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents

Feng, S., Patel, S. S., Wan, H., & Joshi, S. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Speech and dialogue systemsTopic Modeling

Cited by 44