Check computer science papers: citations, claims and retractions

Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning

Jernite, Y., Bowman, S. R., & Sontag, D. (2017) · arXiv

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 101

Following the sun: Case studies in global software development

Treinen, J. J., & Miller-Frost, S. L. (2006) · IBM Systems Journal

Software Engineering Techniques and PracticesTeam Dynamics and Performance

Cited by 101

Towards investigating the validity of measurement of self-regulated learning based on trace data

Fan, Y., van der Graaf, J., Lim, L., Raković, M., Singh, S., Kilgour, J., Moore, J., Molenaar, I., Bannert, M., & Gašević, D. (2022) · Metacognition and Learning

Online Learning and AnalyticsInnovative Teaching and Learning Methods

Cited by 101

Evolution of integrated causal structures in animats exposed to environments of increasing complexity

Albantakis, L., Hintze, A., Koch, C., Adami, C., & Tononi, G. (2014) · PLoS Computational Biology

Evolutionary Algorithms and ApplicationsEmbodied and Extended Cognition

Cited by 101

YOLOv3 and YOLOv4: Multiple Object Detection for Surveillance Applications

Kumar B., C., Punitha, R., & Mohana (2020) · 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 101

Reveal, Don’t Conceal: Transforming Data Visualization to Improve Transparency

Weissgerber, T. L., Winham, S. J., Heinzen, E. P., Milin-Lazovic, J. S., Garcia-Valencia, O., Bukumiric, Z., Savic, M. D., Garovic, V. D., & Milic, N. M. (2019) · Circulation

Data Visualization and AnalyticsAcademic Writing and Publishing

Cited by 101

A Survey of Generative AI Applications

Gozalo-Brizuela, R., & Merchan, E. E. G. (2024) · Journal of Computer Science

Artificial Intelligence ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 101

Generating Instruction Automatically for the Reading Strategy of Self-Questioning

Jack, M., & Wei, C. (2009) · Frontiers in Artificial Intelligence and Applications

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 101

GenAICHI: Generative AI and HCI

Muller, M., Chilton, L. B., Kantosalo, A., Martin, C. P., & Walsh, G. (2022) · CHI Conference on Human Factors in Computing Systems Extended Abstracts

Innovative Human-Technology InteractionDigital Media and Visual Art

Cited by 101

Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets

Chen, J. H., Alagappan, M., Goldstein, M. K., Asch, S. M., & Altman, R. B. (2017) · International Journal of Medical Informatics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 101

Multi-scale structured CNN with label consistency for brain MR image segmentation

Bao, S., & Chung, A. C. S. (2018) · Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 101

The Disagreement Deconvolution: Bringing Machine Learning Performance Metrics In Line With Reality

Gordon, M. L., Zhou, K., Patel, K., Hashimoto, T., & Bernstein, M. S. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Hate Speech and Cyberbullying DetectionMachine Learning and Data Classification

Cited by 101

A Survey on Speech Deepfake Detection

Li, M., Ahmadiadli, Y., & Zhang, X.-P. (2025) · ACM Computing Surveys

Speech Recognition and SynthesisDigital Media Forensic Detection

Cited by 101

A logarithmic-depth quantum carry-lookahead adder

Draper, T. G., Kutin, S. A., Rains, E. M., & Svore, K. M. (2006) · Quantum Information and Computation

Quantum Computing Algorithms and ArchitectureCryptography and Residue Arithmetic

Cited by 101

Entity-Based Knowledge Conflicts in Question Answering

Longpre, S., Perisetla, K., Chen, A., Ramesh, N., DuBois, C., & Singh, S. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingMultimodal Machine Learning Applications

Cited by 101

Quantum neural network

Altaisky, M. V. (2001) · arXiv

Quantum Computing Algorithms and ArchitectureNeural Networks and Reservoir Computing

Cited by 101

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback

Casper, S., Davies, X., Shi, C., Gilbert, T. K., Scheurer, J., Rando, J., Freedman, R., Korbak, T., Lindner, D., Freire, P., et al. (2023) · arXiv

Reinforcement Learning in RoboticsPsychiatry, Mental Health, Neuroscience

Cited by 101

A review on the self and dual interactions between machine learning and optimisation

Song, H., Triguero, I., & Özcan, E. (2019) · Progress in Artificial Intelligence

Metaheuristic Optimization Algorithms ResearchStochastic Gradient Optimization Techniques

Cited by 101

A Review of Anonymization for Healthcare Data

Olatunji, I. E., Rauch, J., Katzensteiner, M., & Khosla, M. (2024) · Big Data

Privacy-Preserving Technologies in DataThoreau and American Literature

Cited by 101

Interactive Model Cards: A Human-Centered Approach to Model Documentation

Crisan, A., Drouhard, M., Vig, J., & Rajani, N. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 101

Overview: Real-Time Protocols for Browser-Based Applications

Alvestrand, H. (2021)

Mobile and Web ApplicationsNetwork Traffic and Congestion Control

Cited by 101

Implementing Ethics in Healthcare AI-Based Applications: A Scoping Review

Goirand, M., Austin, E., & Clay-Williams, R. (2021) · Science and Engineering Ethics

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 101

Smartphone apps in the COVID-19 pandemic

Pandit, J. A., Radin, J. M., Quer, G., & Topol, E. J. (2022) · Nature Biotechnology

COVID-19 Digital Contact TracingMobile Health and mHealth Applications

Cited by 101

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Shao, Z., Wang, P., Zhu, Q., Xu, R., Song, J., Bi, X., Zhang, H., Zhang, M., Li, Y. K., Wu, Y., et al. (2024) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 101