Check computer science papers: citations, claims and retractions

Training large language models on narrow tasks can lead to broad misalignment

Betley, J., Warncke, N., Sztyber-Betley, A., Tan, D., Bao, X., Soto, M., Srivastava, M., Labenz, N., & Evans, O. (2026) · Nature

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 31

Vehicle Detection Based on Drone Images with the Improved Faster R-CNN

Wang, L., Liao, J., & Xu, C. (2019) · Proceedings of the 2019 11th International Conference on Machine Learning and Computing

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 31

SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering

Yang, J., Jimenez, C. E., Wettig, A., Lieret, K., Yao, S., Narasimhan, K., & Press, O. (2024) · arXiv

Multi-Agent Systems and NegotiationScheduling and Optimization Algorithms

Cited by 31

Insider Threat Identification Using the Simultaneous Neural Learning of Multi-Source Logs

Liu, L., Chen, C., Zhang, J., De Vel, O., & Xiang, Y. (2019) · IEEE Access

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 31

Data provenance in healthcare: approaches, challenges, and future directions

Ahmed, M., Dar, A. R., Helfert, M., Khan, A., & Kim, J. (2023) · Sensors

Blockchain Technology Applications and SecurityElectronic Health Records Systems

Cited by 31

Economic Issues in Bitcoin Mining and Blockchain Research

Qin, R., Yuan, Y., Wang, S., & Wang, F.-Y. (2018) · 2018 IEEE Intelligent Vehicles Symposium (IV)

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 31

Agent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systems

Abuelsaad, T., Akkil, D., Dey, P., Jagmohan, A., Vempaty, A., & Kokku, R. (2024) · arXiv

Web Data Mining and AnalysisInformation Retrieval and Search Behavior

Cited by 31

Advanced Smart Contract Vulnerability Detection via LLM-Powered Multi-Agent Systems

Wei, Z., Sun, J., Sun, Y., Liu, Y., Wu, D., Zhang, Z., Zhang, X., Li, M., Liu, Y., Li, C., et al. (2025) · IEEE Transactions on Software Engineering

Blockchain Technology Applications and SecuritySoftware Testing and Debugging Techniques

Cited by 31

Missing-modality enabled multi-modal fusion architecture for medical data

Wang, M., Fan, S., Li, Y., Xie, Z., & Chen, H. (2025) · Journal of Biomedical Informatics

Multimodal Machine Learning ApplicationsMachine Learning in Healthcare

Cited by 31

Improvised Theatre Alongside Artificial Intelligences

Mathewson, K., & Mirowski, P. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment

Speech and dialogue systemsSocial Robot Interaction and HRI

Cited by 31

WebArena: A Realistic Web Environment for Building Autonomous Agents

Zhou, S., Xu, F. F., Zhu, H., Zhou, X., Lo, R., Sridhar, A., Cheng, X., Ou, T., Bisk, Y., Fried, D., et al. (2023) · arXiv

Software Testing and Debugging TechniquesWeb Data Mining and Analysis

Cited by 31

vTC: Machine Learning Based Traffic Classification as a Virtual Network Function

He, L., Xu, C., & Luo, Y. (2016) · Proceedings of the 2016 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization

Software-Defined Networks and 5GInternet Traffic Analysis and Secure E-voting

Cited by 31

Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions

Chen, H., Fang, Z., Singla, Y., & Dredze, M. (2025) · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 31

Automatic detection of anomalies in blood glucose using a machine learning approach

Zhu, Y. (2011) · Journal of Communications and Networks

Anomaly Detection Techniques and ApplicationsArtificial Intelligence in Healthcare

Cited by 31

Enterprise cognitive computing applications – Opportunities and challenges

Tarafdar, M., Beath, C. M., & Ross, J. W. (2017) · IT Professional

Artificial Intelligence ApplicationsCognitive Computing and Networks

Cited by 31

GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation

Chen, E., Lee, J.-E., Lin, J., & Koedinger, K. (2024) · Proceedings of the Eleventh ACM Conference on Learning @ Scale

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 31

Protecting Semantic Trajectory Privacy for VANET with Reinforcement Learning

Wang, W., Min, M., Xiao, L., Chen, Y., & Dai, H. (2019) · ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

Privacy-Preserving Technologies in DataVehicular Ad Hoc Networks (VANETs)

Cited by 31

ReFT: Reasoning with Reinforced Fine-Tuning

Trung, L., Zhang, X., Jie, Z., Sun, P., Jin, X., & Li, H. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 31

Analysis of anomaly detection method for Internet of things based on deep learning

Ma, W. (2020) · Transactions on Emerging Telecommunications Technologies

Anomaly Detection Techniques and ApplicationsNetwork Security and Intrusion Detection

Cited by 31

Quantum-mechanical computers and uncomputability

Lloyd, S. (1993) · Physical Review Letters

Computability, Logic, AI AlgorithmsQuantum Computing Algorithms and Architecture

Cited by 31

DBSP: Automatic Incremental View Maintenance for Rich Query Languages

Budiu, M., Chajed, T., McSherry, F., Ryzhyk, L., & Tannen, V. (2023) · Proceedings of the VLDB Endowment

Advanced Database Systems and QueriesData Management and Algorithms

Cited by 31

Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?

Xiong, Y., Mehta, R., & Singh, V. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 31

PneumoLLM: Harnessing the power of large language model for pneumoconiosis diagnosis

Song, M., Wang, J., Yu, Z., Wang, J., Yang, L., Lu, Y., Li, B., Wang, X., Wang, X., Huang, Q., et al. (2024) · Medical Image Analysis

Multimodal Machine Learning ApplicationsCOVID-19 diagnosis using AI

Cited by 31

Review of autonomous systems and collaborative AI agent frameworks

Joshi, S. (2025) · International Journal of Science and Research Archive

Artificial Intelligence ApplicationsMulti-Agent Systems and Negotiation

Cited by 31