Check computer science papers: citations, claims and retractions

Out of the Cage: How Stochastic Parrots Win in Cyber Security Environments

Rigaki, M., Lukáš, O., Catania, C., & Garcia, S. (2024) · Proceedings of the 16th International Conference on Agents and Artificial Intelligence

Network Security and Intrusion DetectionAdversarial Robustness in Machine Learning

Cited by 17

Meltdown

Lipp, M., Schwarz, M., Gruss, D., Prescher, T., Haas, W., Mangard, S., Kocher, P., Genkin, D., Yarom, Y., & Hamburg, M. (2018) · arXiv

Security and Verification in ComputingCryptographic Implementations and Security

Cited by 17

Chinese medicine prescription recommendation using generative adversarial network

Rong, C., Li, X., Sun, X., & Sun, H. (2022) · IEEE Access

Generative Adversarial Networks and Image SynthesisTraditional Chinese Medicine Studies

Cited by 17

Analysis of a Fault-Tolerant Framework for Reliability Prediction of Service-Oriented Architecture Systems

Chiang, M.-C., Huang, C.-Y., Wu, C.-Y., & Tsai, C.-Y. (2021) · IEEE Transactions on Reliability

Software Reliability and Analysis ResearchReliability and Maintenance Optimization

Cited by 17

Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards

Huang, Y., Nasr, M., Angelopoulos, A., Carlini, N., Chiang, W.-L., Choquette-Choo, C. A., Ippolito, D., Jagielski, M., Lee, K., Liu, K. Z., et al. (2025) · arXiv

Adversarial Robustness in Machine LearningSpam and Phishing Detection

Cited by 17

Spectral-gap analysis for efficient tunneling in quantum adiabatic optimization

Brady, L. T., & van Dam, W. (2016) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 17

FedFSA: Hybrid and federated framework for functional status ascertainment across institutions

Fu, S., Jia, H., Vassilaki, M., Keloth, V. K., Dang, Y., Zhou, Y., Garg, M., Petersen, R. C., St Sauver, J., Moon, S., et al. (2024) · Journal of Biomedical Informatics

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 17

Multimodal continuous affect recognition based on LSTM and multiple kernel learning

Wei, J., Pei, E., Jiang, D., Sahli, H., Xie, L., & Fu, Z. (2014) · Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 17

The impact of text topic and assumed human vs. AI authorship on competence and quality assessment

Proksch, S., Schühle, J., Streeb, E., Weymann, F., Luther, T., & Kimmerle, J. (2024) · Frontiers in Artificial Intelligence

Ethics and Social Impacts of AIAuthorship Attribution and Profiling

Cited by 17

GPTuner: An LLM-Based Database Tuning System

Lao, J., Wang, Y., Li, Y., Wang, J., Zhang, Y., Cheng, Z., Chen, W., Tang, M., & Wang, J. (2025) · ACM SIGMOD Record

Advanced Database Systems and QueriesSoftware System Performance and Reliability

Cited by 17

Critical Correlation of Predictors for an Efficient Risk Prediction Framework of ICU Patient Using Correlation and Transformation of MIMIC-III Dataset

Khope, S. R., & Elias, S. (2022) · Data Science and Engineering

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 17

Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs

Nguyen, T., Luo, L., Shiri, F., Phung, D., Li, Y.-F., Vu, T.-T., & Haffari, G. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingMultimodal Machine Learning Applications

Cited by 17

A layered defense mechanism for a social engineering aware perimeter

Abeywardana, K. Y., Pfluegel, E., & Tunnicliffe, M. J. (2016) · 2016 SAI Computing Conference (SAI)

Information and Cyber SecuritySpam and Phishing Detection

Cited by 17

Decomposition of split-step quantum walks for simulating Majorana modes and edge states

Zhang, W.-W., Goyal, S. K., Simon, C., & Sanders, B. C. (2017) · Physical Review A

Quantum Computing Algorithms and ArchitectureTopological Materials and Phenomena

Cited by 17

Retrieval-Free Knowledge-Grounded Dialogue Response Generation with Adapters

Xu, Y., Ishii, E., Cahyawijaya, S., Liu, Z., Winata, G. I., Madotto, A., Su, D., & Fung, P. (2021) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 17

Reply to: No specific relationship between hypnotic suggestibility and the rubber hand illusion

Lush, P., & Seth, A. K. (2022) · Nature Communications

Virtual Reality Applications and ImpactsFree Will and Agency

Cited by 17

Contrastive Audio-Language Learning for Music

Manco, I., Benetos, E., Quinton, E., & Fazekas, G. (2022) · arXiv

Music and Audio ProcessingMultimodal Machine Learning Applications

Cited by 17

Access to digital media and devices among adolescents in sub‐Saharan Africa: A multicountry, school‐based survey

Wang, D., Shinde, S., Drysdale, R., Vandormael, A., Tadesse, A. W., Sherfi, H., Tinkasimile, A., Mwanyika‐Sando, M., Moshabela, M., Bärnighausen, T., et al. (2025) · Maternal & Child Nutrition

ICT in Developing CommunitiesImpact of Technology on Adolescents

Cited by 17

Deep Blue: A Fuzzy Q-Learning Enhanced Active Queue Management Scheme

Masoumzadeh, S. S., Taghizadeh, G., Meshgi, K., & Shiry, S. (2009) · 2009 International Conference on Adaptive and Intelligent Systems

Network Traffic and Congestion ControlSoftware-Defined Networks and 5G

Cited by 17

Quantitative Impact Evaluation of an Abstraction Layer for Data Stream Processing Systems

Hesse, G., Matthies, C., Glass, K., Huegle, J., & Uflacker, M. (2019) · 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)

Advanced Database Systems and QueriesCloud Computing and Resource Management

Cited by 17

Multi-Agent Systems: Technical & Ethical Challenges of Functioning in a Mixed Group

Gal, K., & Grosz, B. J. (2022) · Daedalus

Multi-Agent Systems and NegotiationEthics and Social Impacts of AI

Cited by 17

Strictly Batch Imitation Learning by Energy-based Distribution Matching

Jarrett, D., Bica, I., & van der Schaar, M. (2020) · arXiv

Reinforcement Learning in RoboticsMachine Learning and Algorithms

Cited by 17

Gender-tuning: Empowering Fine-tuning for Debiasing Pre-trained Language Models

Ghanbarzadeh, S., Huang, Y., Palangi, H., Cruz Moreno, R., & Khanpour, H. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Ethics and Social Impacts of AITopic Modeling

Cited by 17

Finding Inductive Loop Invariants using Large Language Models

Kamath, A., Senthilnathan, A., Chakraborty, S., Deligiannis, P., Lahiri, S. K., Lal, A., Rastogi, A., Roy, S., & Sharma, R. (2023) · arXiv

Logic, programming, and type systemsFormal Methods in Verification

Cited by 17