Check computer science papers: citations, claims and retractions

Uses and Misuses of ChatGPT by Academic Community: An Overview and Guidelines

Abbas, M. (2023) · SSRN Electronic Journal

Ethics and Social Impacts of AIAcademic integrity and plagiarism

Cited by 13

Quantum Transfer Learning Approach for Deepfake Detection

Mishra, B., & Samanta, A. (2022) · Sparklinglight Transactions on Artificial Intelligence and Quantum Computing

Digital Media Forensic DetectionFace recognition and analysis

Cited by 13

Towards Resolving Unidentifiability in Inverse Reinforcement Learning

Amin, K., & Singh, S. (2016) · arXiv

Reinforcement Learning in RoboticsMachine Learning and Algorithms

Cited by 13

Learning and Acting in Peripersonal Space: Moving, Reaching, and Grasping

Juett, J., & Kuipers, B. (2019) · Frontiers in Neurorobotics

Reinforcement Learning in RoboticsEmbodied and Extended Cognition

Cited by 13

CoughLIME: Sonified Explanations for the Predictions of COVID-19 Cough Classifiers

Wullenweber, A., Akman, A., & Schuller, B. W. (2022) · 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

Explainable Artificial Intelligence (XAI)COVID-19 diagnosis using AI

Cited by 13

Encoding and Recall of Spatio-Temporal Episodic Memory in Real Time

Chang, P.-H., & Tan, A.-H. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

Neural Networks and ApplicationsCognitive Computing and Networks

Cited by 13

Automated segmentation of insect anatomy from micro‐CT images using deep learning

Toulkeridou, E., Gutierrez, C. E., Baum, D., Doya, K., & Economo, E. P. (2023) · Natural Sciences

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 13

Fault Localization for Microservice Applications with System Logs and Monitoring Metrics

Zhang, Q., Jia, T., Wu, Z., Wu, Q., Jia, L., Li, D., Tao, Y., & Xiao, Y. (2022) · 2022 7th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA)

Software System Performance and ReliabilitySoftware Testing and Debugging Techniques

Cited by 13

Reasoning about causality in games

Hammond, L., Fox, J., Everitt, T., Carey, R., Abate, A., & Wooldridge, M. (2023) · Artificial Intelligence

Bayesian Modeling and Causal InferenceLogic, Reasoning, and Knowledge

Cited by 13

Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs

Ge, S., Zhang, Y., Liu, L., Zhang, M., Han, J., & Gao, J. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 13

Decoding quantum color codes with MaxSAT

Berent, L., Burgholzer, L., Derks, P.-J. H. S., Eisert, J., & Wille, R. (2024) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 13

Learning and Retrieval from Prior Data for Skill-based Imitation Learning

Nasiriany, S., Gao, T., Mandlekar, A., & Zhu, Y. (2022) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 13

ImpactTracer: Root Cause Localization in Microservices Based on Fault Propagation Modeling

Xie, R., Yang, J., Li, J., & Wang, L. (2023) · 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)

Software System Performance and ReliabilitySoftware Engineering Research

Cited by 13

JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents

Zheng, K., Zhou, K., Gu, J., Fan, Y., Wang, J., Di, Z., He, X., & Wang, X. E. (2022) · arXiv

Speech and dialogue systemsAI-based Problem Solving and Planning

Cited by 13

“Improve the accuracy of students admission at universities using machine learning techniques,”

Assiri, B., Bashraheel, M., & Alsuri, A. (2022) · 2022 7th International Conference on Data Science and Machine Learning Applications (CDMA)

Online Learning and AnalyticsData Mining and Machine Learning Applications

Cited by 13

Communicating Patient Health Data: A Wicked Problem

Rajabiyazdi, F., Perin, C., Oehlberg, L., & Carpendale, S. (2021) · IEEE Computer Graphics and Applications

Data Visualization and AnalyticsElectronic Health Records Systems

Cited by 13

Background Reconstruction via 3D-Transformer Network for Hyperspectral Anomaly Detection

Wu, Z., & Wang, B. (2023) · Remote Sensing

Remote-Sensing Image ClassificationSatellite Image Processing and Photogrammetry

Cited by 13

Exploiting the Signal-Leak Bias in Diffusion Models

Everaert, M. N., Fitsios, A., Bocchio, M., Arpa, S., Süsstrunk, S., & Achanta, R. (2024) · 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 13

The Quantum Alternating Operator Ansatz for Satisfiability Problems

Golden, J., Bärtschi, A., O'Malley, D., & Eidenbenz, S. (2023) · 2023 IEEE International Conference on Quantum Computing and Engineering (QCE)

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 13

Sim-to-Real in Reinforcement Learning for Everyone

Vacaro, J., Marques, G., Oliveira, B., Paz, G., Paula, T., Staehler, W., & Murphy, D. (2019) · 2019 Latin American Robotics Symposium (LARS), 2019 Brazilian Symposium on Robotics (SBR) and 2019 Workshop on Robotics in Education (WRE)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 13

Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?

Blum, A., & Stangl, K. (2019) · arXiv

Ethics and Social Impacts of AIPrivacy-Preserving Technologies in Data

Cited by 13

SuperLocalMemory: Privacy-Preserving Multi-Agent Memory with Bayesian Trust Defense Against Memory Poisoning

Bhardwaj, V. P. (2026) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 13

Bit-shrinking: Limiting Instantaneous Sharpness for Improving Post-training Quantization

Lin, C., Peng, B., Li, Z., Tan, W., Ren, Y., Xiao, J., & Pu, S. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 13

Meta-learning reduces the amount of data needed to build AI models in oncology

Gevaert, O. (2021) · British Journal of Cancer

Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education

Cited by 13