Check computer science papers: citations, claims and retractions

Empowering Working Memory for Large Language Model Agents

Guo, J., Li, N., Qi, J., Yang, H., Li, R., Feng, Y., Zhang, S., & Xu, M. (2023) · arXiv

Psychiatry, Mental Health, NeuroscienceTopic Modeling

Cited by 4

The hidden functions of sycophancy in AI systems: steering, consistency, and cognitive dependency

Jacobowitz, S. (2026) · AI & SOCIETY

Ethics and Social Impacts of AIAI in Service Interactions

Cited by 4

Genetic Insights into the Economic Toll of Cell Line Misidentification: A Comprehensive Review

Weiskirchen, R. (2026) · Medical Sciences

Research Data Management PracticesIdentification and Quantification in Food

Cited by 4

Artificial Intelligence in Research and Development

Jones, B. (2025) · National Bureau of Economic Research

Artificial Intelligence ApplicationsEconomic Growth and Productivity

Cited by 4

Learning with sparse reward in a gap junction network inspired by the insect mushroom body

Wei, T., Guo, Q., & Webb, B. (2024) · PLOS Computational Biology

Reinforcement Learning in RoboticsNeurobiology and Insect Physiology Research

Cited by 4

Current work in diversity, inclusion and accessibility by metadata communities: a working report from the ALA/ALCTS metadata standards committee

Bolam, M. R., Corbett, L. E., Ellero, N. P., Stein Kenfield, A., Mitchell, E. T., Opasik, S. A., & Ryszka, D. (2018) · Technical Services Quarterly

Library Science and Information SystemsLibrary Science and Administration

Cited by 4

Thinking beyond the anthropomorphic paradigm benefits LLM research

Ibrahim, L., & Cheng, M. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

Use of formative assessment to improve the online teaching materials content quality

Zarqtouni, M., Haddi, A., & Allali, H. (2020) · Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications

Online Learning and AnalyticsStudent Assessment and Feedback

Cited by 3

Why do classifier accuracies show linear trends under distribution shift?

Mania, H., & Sra, S. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 3

Hierarchical Reasoning Model

Wang, G., Li, J., Sun, Y., Chen, X., Liu, C., Wu, Y., Lu, M., Song, S., & Yadkori, Y. A. (2025) · arXiv

AI-based Problem Solving and PlanningTopic Modeling

Cited by 3

BS-Net: A Behavior Sequence Network for Insider Threat Detection

Zhu, D., Sun, H., Li, N., Mi, B., & Xi, T. (2021) · 2021 IEEE Symposium on Computers and Communications (ISCC)

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 3

INTERFACILE: linguistic coverage and query reformulation

Mathieu, Y., & Sabatier, P. (1986) · Proceedings of the 11th coference on Computational linguistics -

Natural Language Processing TechniquesInformation Retrieval and Search Behavior

Cited by 3

PatchTrack: Analyzing ChatGPT's Impact on Software Patch Decision-Making in Pull Requests

Ogenrwot, D., & Businge, J. (2024) · Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 3

Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale

Bonatti, R., Zhao, D., Bonacci, F., Dupont, D., Abdali, S., Li, Y., Lu, Y., Wagle, J., Koishida, K., Bucker, A., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsInformation Retrieval and Search Behavior

Cited by 3

On the Impacts of Contexts on Repository-Level Code Generation

Hai, N. L., Nguyen, D. M., & Bui, N. D. Q. (2024) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 3

Digital Doppelgangers: Ethical and Societal Implications of Pre-Mortem AI Clones

Methuku, V., & Myakala, P. K. (2025) · arXiv

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 3

Learning Knowledge Graph Embeddings with Type Regularizer

Kotnis, B., & Nastase, V. (2017) · Proceedings of the Knowledge Capture Conference

Advanced Graph Neural NetworksTopic Modeling

Cited by 3

Learning to Act from Actionless Videos through Dense Correspondences

Ko, P.-C., Mao, J., Du, Y., Sun, S.-H., & Tenenbaum, J. B. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 3

Large Language Model Reasoning Failures

Song, P., Han, P., & Goodman, N. (2026) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 3

From designer to curator: cognitive and creative trade-offs in GenAI-assisted design

Jang, S. Y. (2026) · Fashion and Textiles

Digital Media and Visual ArtCultural and Historical Studies

Cited by 3

Belief in the Machine: Investigating Epistemological Blind Spots of Language Models

Suzgun, M., Gur, T., Bianchi, F., Ho, D. E., Icard, T., Jurafsky, D., & Zou, J. (2024) · arXiv

Logic, Reasoning, and KnowledgeTopic Modeling

Cited by 3

AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving

Xing, S., Hua, H., Gao, X., Zhu, S., Li, R., Tian, K., Li, X., Huang, H., Yang, T., Wang, Z., et al. (2024) · arXiv

Explainable Artificial Intelligence (XAI)Adversarial Robustness in Machine Learning

Cited by 3

Mathematical exploration and discovery at scale

Georgiev, B., Gómez-Serrano, J., Tao, T., & Wagner, A. Z. (2025) · arXiv

Evolutionary Algorithms and ApplicationsArtificial Intelligence Applications

Cited by 3

Open-Source vs. Commercial Coding Assistants: A 2025 Comparison of DeepSeek R1, Qwen 2.5 and Claude 3.7

Joshi, S. B. (2025) · International Journal of Computer Applications Technology and Research

Software Engineering ResearchTopic Modeling

Cited by 3