Check computer science papers: citations, claims and retractions

Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

Zhou, H., Chen, Y., Guo, S., Yan, X., Lee, K. H., Wang, Z., Lee, K. Y., Zhang, G., Shao, K., Yang, L., et al. (2025) · arXiv

Domain Adaptation and Few-Shot LearningReinforcement Learning in Robotics

Cited by 2

Sacred or Synthetic? Evaluating LLM Reliability and Abstention for Religious Questions

Atif, F., Askarbekuly, N., Darwish, K., & Choudhury, M. (2025) · Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society

Topic ModelingArtificial Intelligence in Law

Cited by 2

Normalizer: Augmenting Code Clone Detectors using Source Code Normalization

Ly, K. (2019)

Software Engineering ResearchAcademic integrity and plagiarism

Cited by 2

AIP: Agent Identity Protocol for Verifiable Delegation Across MCP and A2A

Prakash, S. (2026) · arXiv

Access Control and TrustAdvanced Authentication Protocols Security

Cited by 2

CodeCleaner: Mitigating Data Contamination for LLM Benchmarking

Cao, J., Chen, S., Zhang, W., Lo, H. C., Li, Y., & Cheung, S.-C. (2025) · Proceedings of the 16th International Conference on Internetware

Software Engineering ResearchTopic Modeling

Cited by 2

Vision-Guided Iterative Refinement for Frontend Code Generation

Sansford, H., Law, D. H. C., Liu, W., Tripathi, A., Agarwal, N., & Burg, G. J. J. V. D. (2026) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 2

Workflow Automation in Open-Source Software Development: Accelerating Innovation Through Mechanization and Orchestration

Huang, A., Huang, N., & Hong, Y. (2026) · Information Systems Research

Open Source Software InnovationsSoftware Engineering Techniques and Practices

Cited by 2

How Students Use AI Feedback Matters: Experimental Evidence on Physics Achievement and Autonomy

Dai, X., Wen, Z., Jiang, J., Liu, H., & Zhang, Y. (2025) · arXiv

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 2

Conditional Energy-Based Models for Implicit Policies: The Gap between Theory and Practice

Ta, D.-N., Cousineau, E., Zhao, H., & Feng, S. (2022) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 2

Development and Validation of Computable Social Phenotypes for Health‐Related Social Needs

Gregory, M. E., Kasthurirathne, S. N., Magoc, T., McNamee, C., Harle, C. A., & Vest, J. R. (2024) · JAMIA Open

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 2

Mammoth2: Scaling instructions from the web

Yue, X., Zheng, T., Zhang, G., & Chen, W. (2024) · Advances in Neural Information Processing Systems 37

Natural Language Processing TechniquesTopic Modeling

Cited by 2

Simulating Human-like Daily Activities with Desire-driven Autonomy

Wang, Y., Chen, Y., Zhong, F., Ma, L., & Wang, Y. (2024) · arXiv

Psychiatry, Mental Health, NeuroscienceAI-based Problem Solving and Planning

Cited by 2

R-Judge: Benchmarking Safety Risk Awareness for LLM Agents

Yuan, T., He, Z., Dong, L., Wang, Y., Zhao, R., Xia, T., Xu, L., Zhou, B., Li, F., Zhang, Z., et al. (2024) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 2

Archives of Thrill: The V-Armchair Experience

Passmore, P. J., Tennent, P., Walker, B., Philpot, A., Le, H., Markowski, M., & Karamanoglu, M. (2017) · The Eurographics Association

Virtual Reality Applications and ImpactsTechnology Use by Older Adults

Cited by 2

BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting

Yong, Z.-X., Schoelkopf, H., Muennighoff, N., Aji, A. F., Adelani, D. I., Almubarak, K., Bari, M. S., Sutawika, L., Kasai, J., Baruwa, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

Symbolic Representation for Any-to-Any Generative Tasks

Chen, J., Zhu, X., Wang, Y., Liu, T., Chen, X., Chen, Y., Leong, C. T., Ke, Y., Liu, J., Yuan, Y., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 2

MoMA: a mixture-of-multimodal-agents architecture for enhancing clinical prediction modelling

Gao, J., Rahman, M., Caskey, J., Oguss, M., O’Rourke, A., Brown, R., Stey, A., Mayampurath, A., Churpek, M. M., Chen, G., et al. (2025) · npj Digital Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 2

Blockchain Technology for the Security of Internet of Things: Challenges, Solutions, and Future Trends

Khan, M. U. (2023)

Blockchain Technology Applications and SecurityIoT and Edge/Fog Computing

Cited by 2

Evaluating Self-Supervised Learning Methods for Downstream Classification of Neoplasia in Barrett’s Esophagus

Cornelissen, S., van der Putten, J. A., Boers, T. G. W., Jukema, J. B., Fockens, K. N., Bergman, J. J. G. H. M., van der Sommen, F., & de With, P. H. N. (2021) · 2021 IEEE International Conference on Image Processing (ICIP)

Domain Adaptation and Few-Shot LearningAI in cancer detection

Cited by 2

Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning

Wang, H., Unsal, M., Lin, X., Baksys, M., Liu, J., Santos, M. D., Sung, F., Vinyes, M., Ying, Z., Zhu, Z., et al. (2025) · arXiv

Logic, programming, and type systemsMathematics, Computing, and Information Processing

Cited by 2

Exploring Transformer Extrapolation

Qin, Z., Zhong, Y., & Deng, H. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments

Su, H., Sun, R., Yoon, J., Yin, P., Yu, T., & Arık, S. Ö. (2025) · arXiv

Topic ModelingSoftware Engineering Research

Cited by 2

Post-quantum XML and SAML Single Sign-On

Müller, J., & Oupický, J. (2024) · Proceedings on Privacy Enhancing Technologies

Cryptography and Data SecurityQuantum Information and Cryptography

Cited by 2

A hybrid control scheme for facial rigging

Liu, B., & Davis, T. A. (2013) · Proceedings of CGAMES'2013 USA

Human Motion and AnimationComputer Graphics and Visualization Techniques

Cited by 2