Check computer science papers: citations, claims and retractions

Beyond Goldfish Memory: Long-Term Open-Domain Conversation

Xu, J., Szlam, A., & Weston, J. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Speech and dialogue systemsTopic Modeling

Cited by 188

Multi-task Learning based Pre-trained Language Model for Code Completion

Liu, F., Li, G., Zhao, Y., & Jin, Z. (2020) · Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

Software Engineering ResearchTopic Modeling

Cited by 188

Designing for the dynamics of cooperative work activities

Bardram, J. (1998) · Proceedings of the 1998 ACM conference on Computer supported cooperative work

Usability and User Interface DesignInformation Systems Theories and Implementation

Cited by 188

Gears of our childhood: constructionist toolkits, robotics, and physical computing, past and future

Blikstein, P. (2013) · Proceedings of the 12th International Conference on Interaction Design and Children

Teaching and Learning ProgrammingArduino and IoT Applications

Cited by 188

REVIEWING THE ETHICAL IMPLICATIONS OF AI IN DECISION MAKING PROCESSES

Osasona, F., Amoo, O. O., Atadoga, A., Abrahams, T. O., Farayola, O. A., & Ayinla, B. S. (2024) · International Journal of Management & Entrepreneurship Research

Ethics and Social Impacts of AIImpact of AI and Big Data on Business and Society

Cited by 188

Fast LIDAR localization using multiresolution Gaussian mixture maps

Wolcott, R. W., & Eustice, R. M. (2015) · 2015 IEEE International Conference on Robotics and Automation (ICRA)

Robotics and Sensor-Based LocalizationAutonomous Vehicle Technology and Safety

Cited by 188

Orchestration of Microservices for IoT Using Docker and Edge Computing

Alam, M., Rufino, J., Ferreira, J., Ahmed, S. H., Shah, N., & Chen, Y. (2018) · IEEE Communications Magazine

IoT and Edge/Fog ComputingCloud Computing and Resource Management

Cited by 188

Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Naseri, M., Hayes, J., & De Cristofaro, E. (2022) · Proceedings 2022 Network and Distributed System Security Symposium

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 188

Virtual reality witness: exploring the ethics of mediated presence

Nash, K. (2018) · Studies in Documentary Film

Virtual Reality Applications and ImpactsLiterature, Film, and Journalism Analysis

Cited by 188

Deep Reinforcement Learning for the Control of Robotic Manipulation: A Focussed Mini-Review

Liu, R., Nageotte, F., Zanne, P., de Mathelin, M., & Dresp-Langley, B. (2021) · Robotics

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 188

Street-Level Algorithms: A Theory at the Gaps Between Policy and Decisions

Alkhatib, A., & Bernstein, M. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AIArtificial Intelligence in Law

Cited by 188

Quantum Computation and Lattice Problems

Regev, O. (2004) · SIAM Journal on Computing

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 188

Beyond Functional Correctness: Exploring Hallucinations in LLM-Generated Code

Liu, F., Liu, Y., Shi, L., Yang, Z., Zhang, L., Lian, X., Li, Z., & Ma, Y. (2024) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 188

DeepIoT: Compressing Deep Neural Network Structures for Sensing Systems with a Compressor-Critic Framework

Yao, S., Zhao, Y., Zhang, A., Su, L., & Abdelzaher, T. (2017) · Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems

Advanced Neural Network ApplicationsIoT and Edge/Fog Computing

Cited by 188

From UI design image to GUI skeleton: a neural machine translator to bootstrap mobile GUI implementation

Chen, C., Su, T., Meng, G., Xing, Z., & Liu, Y. (2018) · Proceedings of the 40th International Conference on Software Engineering

Usability and User Interface DesignSoftware Engineering Research

Cited by 188

Cyber threat detection based on artificial neural networks using event profiles

Lee, J., Kim, J., Kim, I., & Han, K. (2019) · IEEE Access

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 188

The Effects of Image and Animation in Enhancing Pedagogical Agent Persona

Baylor, A. L., & Ryu, J. (2003) · Journal of Educational Computing Research

Intelligent Tutoring Systems and Adaptive LearningVisual and Cognitive Learning Processes

Cited by 188

Physician understanding, explainability, and trust in a hypothetical machine learning risk calculator

Diprose, W. K., Buist, N., Hua, N., Thurier, Q., Shand, G., & Robinson, R. (2020) · Journal of the American Medical Informatics Association

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

Cited by 188

Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud

Wang, J., Zhang, J., Bao, W., Zhu, X., Cao, B., & Yu, P. S. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Privacy-Preserving Technologies in DataCloud Data Security Solutions

Cited by 188

Modeling Trees with a Space Colonization Algorithm

Runions, A., Lane, B., & Prusinkiewicz, P. (2007) · The Eurographics Association

Computer Graphics and Visualization TechniquesGreenhouse Technology and Climate Control

Cited by 188

Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review

Johansson, D., Malmgren, K., & Alt Murphy, M. (2018) · Journal of Neurology

Context-Aware Activity Recognition SystemsStroke Rehabilitation and Recovery

Cited by 188

Virtual Reality Exposure Treatment in Phobias: a Systematic Review

Freitas, J. R. S., Velosa, V. H. S., Abreu, L. T. N., Jardim, R. L., Santos, J. A. V., Peres, B., & Campos, P. F. (2021) · Psychiatric Quarterly

Virtual Reality Applications and ImpactsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Cited by 188

Learning Deep Network Representations with Adversarially Regularized Autoencoders

Yu, W., Zheng, C., Cheng, W., Aggarwal, C. C., Song, D., Zong, B., Chen, H., & Wang, W. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Advanced Graph Neural NetworksComplex Network Analysis Techniques

Cited by 188

Efficient quantum measurement of Pauli operators in the presence of finite sampling error

Crawford, O., Straaten, B. V., Wang, D., Parks, T., Campbell, E., & Brierley, S. (2021) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 188