Check computer science papers: citations, claims and retractions

Combining FastText and Glove Word Embedding for Offensive and Hate speech Text Detection

Badri, N., Kboubi, F., & Chaibi, A. H. (2022) · Procedia Computer Science

Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion Mining

Cited by 65

Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text?

Bhattacharjee, A., & Liu, H. (2024) · ACM SIGKDD Explorations Newsletter

Authorship Attribution and ProfilingTopic Modeling

Cited by 65

Competing or aiming to be average?: normification as a means of engaging digital volunteers

Preist, C., Massung, E., & Coyle, D. (2014) · Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing

Mobile Crowdsensing and CrowdsourcingOpen Source Software Innovations

Cited by 65

Generating and evaluating cross‐sectional synthetic electronic healthcare data: Preserving data utility and patient privacy

Wang, Z., Myles, P., & Tucker, A. (2021) · Computational Intelligence

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 65

DeepFake on Face and Expression Swap: A Review

Waseem, S., Abu Bakar, S. A. R. S., Ahmed, B. A., Omar, Z., Eisa, T. A. E., & Dalam, M. E. E. (2023) · IEEE Access

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 65

When nudge comes to shove: liberty and nudging in the era of big data

Sætra, H. S. (2019) · Technology in Society

Ethics and Social Impacts of AIDecision-Making and Behavioral Economics

Cited by 65

An adaptive display to treat stress-related disorders: EMMA’s World

Baños, R. M., Botella, C., Guillen, V., García-Palacios, A., Quero, S., Bretón-López, J., & Alcañiz, M. (2009) · British Journal of Guidance & Counselling

Virtual Reality Applications and ImpactsPosttraumatic Stress Disorder Research

Cited by 65

Artificial Intelligence Colonialism: Environmental Damage, Labor Exploitation, and Human Rights Crises in the Global South

Regilme, S. S. F. (2024) · SAIS Review of International Affairs

Ethics and Social Impacts of AIExtractivism and Socioeconomic Issues

Cited by 65

CodexDB: synthesizing code for query processing from natural language instructions using GPT-3 codex

Trummer, I. (2022) · Proceedings of the VLDB Endowment

Advanced Database Systems and QueriesSoftware Engineering Research

Cited by 65

An image encryption algorithm based on BP neural network and hyperchaotic system

Yang, F., Mou, J., Cao, Y., & Chu, R. (2020) · China Communications

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 65

Feasibility of a virtual reality intervention in the intensive care unit

Jawed, Y. T., Golovyan, D., Lopez, D., Khan, S. H., Wang, S., Freund, C., Imran, S., Hameed, U. B., Smith, J. P., Kok, L., et al. (2021) · Heart & Lung

Virtual Reality Applications and ImpactsIntensive Care Unit Cognitive Disorders

Cited by 65

Solving Inefficiency of Self-supervised Representation Learning

Wang, G., Wang, K., Wang, G., Torr, P. H. S., & Lin, L. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 65

Remote Sensing Satellite Image Processing Techniques for Image Classification: A Comprehensive Survey

D., S., Deepa, P., & K., V. (2017) · International Journal of Computer Applications

Remote-Sensing Image ClassificationRemote Sensing and Land Use

Cited by 65

MMedAgent: Learning to Use Medical Tools with Multi-modal Agent

Li, B., Yan, T., Pan, Y., Luo, J., Ji, R., Ding, J., Xu, Z., Liu, S., Dong, H., Lin, Z., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 65

Why null results rarely see the light of day

Mervis, J. (2014) · Science

Research Data Management PracticesMeta-analysis and systematic reviews

Cited by 65

A Paradigm Shift in Interactive Computing: Deriving Multimodal Design Principles from Behavioral and Neurological Foundations

Stanney, K., Samman, S., Reeves, L., Hale, K., Buff, W., Bowers, C., Goldiez, B., Nicholson, D., & Lackey, S. (2004) · International Journal of Human-Computer Interaction

Data Visualization and AnalyticsInteractive and Immersive Displays

Cited by 65

Efficient error characterization in quantum information processing

Lévi, B., López, C. C., Emerson, J., & Cory, D. G. (2007) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 65

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Talebirad, Y., & Nadiri, A. (2023) · arXiv

Multi-Agent Systems and NegotiationArtificial Intelligence Applications

Cited by 65

Automatic modeling learner’s personality using learning analytics approach in an intelligent Moodle learning platform

Tlili, A., Denden, M., Essalmi, F., Jemni, M., Chang, M., Kinshuk, & Chen, N.-S. (2023) · Interactive Learning Environments

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 65

Analysis of TF-IDF Model and its Variant for Document Retrieval

Mishra, A., & Vishwakarma, S. (2015) · 2015 International Conference on Computational Intelligence and Communication Networks (CICN)

Information Retrieval and Search BehaviorAlgorithms and Data Compression

Cited by 65

Quantum circuit design for solving linear systems of equations

Cao, Y., Daskin, A., Frankel, S., & Kais, S. (2012) · Molecular Physics

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 65

Semantic Web meets Integrative Biology: a survey

Chen, H., Yu, T., & Chen, J. Y. (2013) · Briefings in Bioinformatics

Semantic Web and OntologiesBiomedical Text Mining and Ontologies

Cited by 65

AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization

Werling, K., Bianco, N. A., Raitor, M., Stingel, J., Hicks, J. L., Collins, S. H., Delp, S. L., & Liu, C. K. (2023) · PLOS ONE

Human Motion and AnimationMuscle activation and electromyography studies

Cited by 65

Computer-aided diagnosis for fetal brain ultrasound images using deep convolutional neural networks

Xie, B., Lei, T., Wang, N., Cai, H., Xian, J., He, M., Zhang, L., & Xie, H. (2020) · International Journal of Computer Assisted Radiology and Surgery

Medical Image Segmentation TechniquesFetal and Pediatric Neurological Disorders

Cited by 65