Check computer science papers: citations, claims and retractions

Collapse or thrive? perils and promises of synthetic data in a self-generating world

Kazdan, J., Schaeffer, R., Dey, A., Gerstgrasser, M., Rafailov, R., Donoho, D. L., & Koyejo, S. (2024) · arXiv

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 4

Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems

Zhang, G., Yue, Y., Li, Z., Yun, S., Wan, G., Wang, K., Cheng, D., Yu, J. X., & Chen, T. (2024) · arXiv

Multi-Agent Systems and NegotiationAdversarial Robustness in Machine Learning

Cited by 4

Design and implementation of the networked video surveillance and management platform in Suzhou subway line 1

Li, B., Tian, B., Li, Y., & Xiong, G. (2013) · Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics

Video Surveillance and Tracking MethodsTechnology and Security Systems

Cited by 4

PyRCA: A Library for Metric-based Root Cause Analysis

Liu, C., Yang, W., Mittal, H., Singh, M., Sahoo, D., & Hoi, S. C. H. (2023) · arXiv

Software System Performance and ReliabilityFault Detection and Control Systems

Cited by 4

FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering

Sui, Y., He, Y., Liu, N., He, X., Wang, K., & Hooi, B. (2024) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 4

UniT: Multimodal Multitask Learning with a Unified Transformer

Hu, R., & Singh, A. (2021) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 4

AutoRAG: Grounding text and symbols

Schulz, T., Luttermann, M., & Möller, R. (2024) · KI - Künstliche Intelligenz

Topic ModelingNatural Language Processing Techniques

Cited by 4

Performance Research on Industrial Demilitarized Zone in Defense-in-Depth Architecture

Jiang, N., Lin, H., Yin, Z., & Zheng, L. (2018) · 2018 IEEE International Conference on Information and Automation (ICIA)

Network Packet Processing and OptimizationNetwork Security and Intrusion Detection

Cited by 4

An RDBMS-only architecture for web applications

Vicente, A., Etcheverry, L., & Sabiguero, A. (2021) · 2021 XLVII Latin American Computing Conference (CLEI)

Web Applications and Data ManagementAdvanced Database Systems and Queries

Cited by 4

A Comparative Study of Android Performance Issues in Real-World Applications and Literature

Liao, D., Pan, S., Yang, S., Zhao, Y., Xing, Z., & Sun, X. (2026) · ACM Transactions on Software Engineering and Methodology

Mobile and Web ApplicationsSoftware System Performance and Reliability

Cited by 4

Learning from lessons learned: preliminary findings from a study of learning from failure

Sillito, J., & Pope, M. (2024) · Proceedings of the 2024 IEEE/ACM 17th International Conference on Cooperative and Human Aspects of Software Engineering

Software Engineering Techniques and PracticesSoftware System Performance and Reliability

Cited by 4

Addressing discrimination in algorithmic profiling: Examining risk governance in Dutch public social security agencies

Haitsma, L. M. (2025) · European Journal of Social Security

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 4

A New Evaluation Model for Information Security Risk Management of SCADA Systems

Lin, K.-S. (2019) · 2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS)

Information and Cyber SecuritySmart Grid Security and Resilience

Cited by 4

AV-Deepfake1M++: A Large-Scale Audio-Visual Deepfake Benchmark with Real-World Perturbations

Cai, Z., Kuckreja, K., Ghosh, S., Chuchra, A., Khan, M. H., Tariq, U., Gedeon, T., & Dhall, A. (2025) · Proceedings of the 33rd ACM International Conference on Multimedia

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 4

Deep Reinforcement Learning with Plasticity Injection

Nikishin, E., Oh, J., Ostrovski, G., Lyle, C., Pascanu, R., Dabney, W., & Barreto, A. (2023) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 4

Development of the Artificial Intelligence Perception and Attitude Scale (AIPAS)

Dinler, H. (2025) · Bartın University Journal of Faculty of Education

Ethics and Social Impacts of AIAI in Service Interactions

Cited by 4

Mitigating Hallucinations in Vision-Language Models through Image-Guided Head Suppression

Sarkar, S., Che, Y., Gavin, A., Beerel, P. A., & Kundu, S. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 4

Governance Matters: Lessons From Restructuring the Data.Table OSS Project

Oliveira, P., Amoakohene, D., Hocking, T., Gerosa, M., & Steinmacher, I. (2025) · 2025 IEEE International Conference on Software Maintenance and Evolution (ICSME)

Open Source Software InnovationsSoftware Engineering Techniques and Practices

Cited by 4

Continual Learning as Computationally Constrained Reinforcement Learning

Kumar, S., Marklund, H., Rao, A., Zhu, Y., Jeon, H. J., Liu, Y., & Van Roy, B. (2023) · arXiv

Domain Adaptation and Few-Shot LearningReinforcement Learning in Robotics

Cited by 4

FABLES: Evaluating faithfulness and content selection in book-length summarization

Kim, Y., Chang, Y., Karpinska, M., Garimella, A., Manjunatha, V., Lo, K., Goyal, T., & Iyyer, M. (2024) · arXiv

Topic ModelingAdvanced Text Analysis Techniques

Cited by 4

HBDCA: A Toolchain for High-Accuracy BRAM-Defined CNN Accelerator on FPGA with Flexible Structure

LI, Z., GAO, J., & LAI, J. (2021) · IEICE Transactions on Information and Systems

Embedded Systems Design TechniquesAdvanced Neural Network Applications

Cited by 4

Child Face Age-Progression via Deep Feature Aging

Deb, D., Aggarwal, D., & Jain, A. K. (2020) · arXiv

Face recognition and analysisBiometric Identification and Security

Cited by 4

Of ChatGPT and Trustworthy AI

Puri, A., & Keymolen, E. (2023) · Journal of Human-Technology Relations

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 4

A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems

Ke, Z., Jiao, F., Ming, Y., Nguyen, X.-P., Xu, A., Long, D. X., Li, M., Qin, C., Wang, P., Savarese, S., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4