Check computer science papers: citations, claims and retractions

Automatic Generation of Multiple-choice Cloze-test Questions for Lao Language Learning

Qiu, X., Xue, H., Liang, L., Xie, Z., Liao, S., & Shi, G. (2021) · 2021 International Conference on Asian Language Processing (IALP)

Natural Language Processing TechniquesTopic Modeling

Cited by 7

Agentic AI for Autonomous Cyber Threat Hunting and Adaptive Defense in Dynamic Security Environments

Sheth, A., Patel, A., Upadhyay, C., Ragothaman, H., Patil, B., & Udayakumar, S. K. (2025) · 2025 IEEE International Conference on Electro Information Technology (eIT)

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 7

Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

Tian, Y., Peng, B., Song, L., Jin, L., Yu, D., Mi, H., & Yu, D. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 7

Learning higher-order sequential structure with cloned HMMs

Dedieu, A., Gothoskar, N., Swingle, S., Lehrach, W., Lázaro-Gredilla, M., & George, D. (2019) · arXiv

Speech Recognition and SynthesisTopic Modeling

Cited by 7

Design Principles and Guidelines for LLM Observability: Insights from Developers

Chen, X., Li, Y., & Wang, X. (2025) · Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

Software System Performance and ReliabilitySoftware Engineering Techniques and Practices

Cited by 7

Relative Feedback Increases Disparities in Effort and Performance in Crowdsourcing Contests: Evidence from a Quasi-Experiment on Topcoder

Tsvetkova, M., Müller, S., Vuculescu, O., Ham, H., & Sergeev, R. A. (2022) · Proceedings of the ACM on Human-Computer Interaction

Mobile Crowdsensing and CrowdsourcingOpen Source Software Innovations

Cited by 7

MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception

Wang, Y., Liao, Y., Liu, H., Liu, H., Wang, Y., & Wang, Y. (2024) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 7

A Survey of Multimodal Large Language Model from A Data-centric Perspective

Bai, T., Liang, H., Wan, B., Xu, Y., Li, X., Li, S., Yang, L., Li, B., Wang, Y., Cui, B., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 7

Non-restricted Access to Model Solutions: A Good Idea?

Nygren, H., Leinonen, J., & Hellas, A. (2019) · Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education

Teaching and Learning ProgrammingInnovative Teaching and Learning Methods

Cited by 7

Semantic search for smart mobile devices

Shin, S., Ko, J., Shin, D.-H., Jung, J., & Lee, K.-H. (2013) · Proceedings of the companion publication of the 2013 international conference on Intelligent user interfaces companion

Semantic Web and OntologiesInformation Retrieval and Search Behavior

Cited by 7

Beyond Presentation: Shared Slideware Control as a Resource for Collocated Collaboration

Chattopadhyay, D., Salvadori, F., O’Hara, K., & Rintel, S. (2018) · Human–Computer Interaction

Interactive and Immersive DisplaysInnovative Human-Technology Interaction

Cited by 7

Classification with LSTM Networks in User Behaviour Analytics with Unbalanced Environment

Parshutin, S., Kirshners, A., Kornijenko, Y., Zabiniako, V., Gasparovica-Asite, M., & Rozkalns, A. (2021) · Automatic Control and Computer Sciences

Imbalanced Data Classification TechniquesAnomaly Detection Techniques and Applications

Cited by 7

Sustainability of Programming Education Through CDIO-Oriented Practice: An Empirical Study on Syntax-Level Structural Visualization for Functional Programming Languages

Lai, C.-H., Ho, L.-C., & Liao, Z.-Y. (2025) · Sustainability

Teaching and Learning ProgrammingProblem and Project Based Learning

Cited by 7

Learning Shallow Neural Networks via Provable Gradient Descent with Random Initialization

Xia, S., & Shi, Y. (2019) · ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Stochastic Gradient Optimization TechniquesNeural Networks and Applications

Cited by 7

Repoformer: Selective Retrieval for Repository-Level Code Completion

Wu, D., Ahmad, W. U., Zhang, D., Ramanathan, M. K., & Ma, X. (2024) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 7

The Importance of Data Citation

Brown, R. F. (2021) · BioScience

Research Data Management PracticesData Analysis and Archiving

Cited by 7

AMEIR: Automatic Behavior Modeling, Interaction Exploration and MLP Investigation in the Recommender System

Zhao, P., Xiao, K., Zhang, Y., Bian, K., & Yan, W. (2021) · Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 7

Embedding Learning with Heterogeneous Event Sequence for Insider Threat Detection

Wang, J., Cai, L., Yu, A., & Meng, D. (2019) · 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 7

Fast Stochastic Recursive Momentum Methods for Imbalanced Data Mining

Wu, X., Huang, F., & Huang, H. (2022) · 2022 IEEE International Conference on Data Mining (ICDM)

Imbalanced Data Classification TechniquesStochastic Gradient Optimization Techniques

Cited by 7

A survey on secure decentralized optimization and learning

Liu, C., Bastianello, N., Huo, W., Shi, Y., & Johansson, K. H. (2024) · arXiv

Privacy-Preserving Technologies in DataDistributed Control Multi-Agent Systems

Cited by 7

Applying a Systematic Literature Review and Content Analysis Method to Analyse Open Source Developers’ Forking Motivation Interpretation, Categories and Consequences

Chua, B. B., & Zhang, Y. (2020) · Australasian Journal of Information Systems

Open Source Software InnovationsSoftware Engineering Techniques and Practices

Cited by 7

What We Know About Using Non-Engagement Signals in Content Ranking

Cunningham, T., Pandey, S., Sigerson, L., Stray, J., Allen, J., Barrilleaux, B., Iyer, R., Milli, S., Kothari, M., & Rezaei, B. (2024) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 7

Low-Rank Representation with Contextual Regularization for Moving Object Detection in Big Surveillance Video Data

Chen, B.-H., Shi, L.-F., & Ke, X. (2017) · 2017 IEEE Third International Conference on Multimedia Big Data (BigMM)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 7

Analysis & Implementation of Personalisation Parameters in the Development of Computer-Based Adaptive Learning Environment

Al-Chalabi, H. K. M., & Ali. Hussein, A. M. (2020) · SAR Journal - Science and Research

Intelligent Tutoring Systems and Adaptive LearningLearning Styles and Cognitive Differences

Cited by 7