Check computer science papers: citations, claims and retractions

A New Path: Scaling Vision-and-Language Navigation with Synthetic Instructions and Imitation Learning

Kamath, A., Anderson, P., Wang, S., Koh, J. Y., Ku, A., Waters, A., Yang, Y., Baldridge, J., & Parekh, Z. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsReinforcement Learning in Robotics

Cited by 39

Extracting Randomness via Repeated Condensing

Reingold, O., Shaltiel, R., & Wigderson, A. (2006) · SIAM Journal on Computing

Computability, Logic, AI AlgorithmsComplexity and Algorithms in Graphs

Cited by 39

Design Rule Spaces: A New Model for Representing and Analyzing Software Architecture

Cai, Y., Xiao, L., Kazman, R., Mo, R., & Feng, Q. (2019) · IEEE Transactions on Software Engineering

Software Engineering ResearchAdvanced Software Engineering Methodologies

Cited by 39

Firefox Voice: An Open and Extensible Voice Assistant Built Upon the Web

Cambre, J., Williams, A. C., Razi, A., Bicking, I., Wallin, A., Tsai, J., Kulkarni, C., & Kaye, J. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Speech and dialogue systemsUsability and User Interface Design

Cited by 39

Assessing Virtual Assistant Capabilities with Italian Dysarthric Speech

Ballati, F., Corno, F., & De Russis, L. (2018) · Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility

Speech Recognition and SynthesisVoice and Speech Disorders

Cited by 39

A Semantic Role-based Approach to Open-Domain Automatic Question Generation

Flor, M., & Riordan, B. (2018) · Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications

Natural Language Processing TechniquesTopic Modeling

Cited by 39

Personalisation methods in e-learning-A literature review

Mikić, V., Ilić, M., Kopanja, L., & Vesin, B. (2022) · Computer Applications in Engineering Education

Intelligent Tutoring Systems and Adaptive LearningEducational Technology and E-Learning

Cited by 39

Language Modeling Is Compression

Delétang, G., Ruoss, A., Duquenne, P.-A., Catt, E., Genewein, T., Mattern, C., Grau-Moya, J., Wenliang, L. K., Aitchison, M., Orseau, L., et al. (2023) · arXiv

Topic ModelingAlgorithms and Data Compression

Cited by 39

Using ChatGPT is easy, using it effectively is tough? A mixed methods study on K-12 students’ perceptions, interaction patterns, and support for learning with generative AI chatbots

Klar, M. (2025) · Smart Learning Environments

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 39

Doo bee doo bee doo

CONVENT, L., LINDLEY, S., MCBRIDE, C., & MCLAUGHLIN, C. (2020) · Journal of Functional Programming

Logic, programming, and type systemsTeaching and Learning Programming

Cited by 39

Explainable AI for Clinical Decision Support Systems: Literature Review, Key Gaps, and Research Synthesis

Salimparsa, M., Sedig, K., Lizotte, D. J., Abdullah, S. S., Chalabianloo, N., & Muanda, F. T. (2025) · Informatics

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 39

Negotiated Finite Field Diffie-Hellman Ephemeral Parameters for Transport Layer Security (TLS)

Gillmor, D. (2016)

Advanced Authentication Protocols SecurityCryptography and Residue Arithmetic

Cited by 39

A Distributional Approach to Controlled Text Generation

Khalifa, M., Elsahar, H., & Dymetman, M. (2020) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 39

Execution-based Code Generation using Deep Reinforcement Learning

Shojaee, P., Jain, A., Tipirneni, S., & Reddy, C. K. (2023) · arXiv

Software Engineering ResearchTeaching and Learning Programming

Cited by 39

Artificial Swarm Intelligence, a Human-in-the-Loop Approach to A.I.

Rosenberg, L. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence

Mobile Crowdsensing and CrowdsourcingDistributed Control Multi-Agent Systems

Cited by 39

Mobile device interaction gestures for older users

Stößel, C., & Blessing, L. (2010) · Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries

Interactive and Immersive DisplaysTechnology Use by Older Adults

Cited by 39

Comparing the Effects of Instructor Manual Feedback and ChatGPT Intelligent Feedback on Collaborative Programming in China's Higher Education

Ouyang, F., Guo, M., Zhang, N., Bai, X., & Jiao, P. (2024) · IEEE Transactions on Learning Technologies

Teaching and Learning ProgrammingIntelligent Tutoring Systems and Adaptive Learning

Cited by 39

Combining chest X-rays and electronic health record (EHR) data using machine learning to diagnose acute respiratory failure

Jabbour, S., Fouhey, D., Kazerooni, E., Wiens, J., & Sjoding, M. W. (2022) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 39

Secure Architectures Implementing Trusted Coalitions for Blockchained Distributed Learning (TCLearn)

Lugan, S., Desbordes, P., Brion, E., Ramos Tormo, L. X., Legay, A., & Macq, B. (2019) · IEEE Access

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 39

Full-Reference Image Quality Assessment with Linear Combination of Genetically Selected Quality Measures

Oszust, M. (2016) · PLOS ONE

Image and Video Quality AssessmentImage Retrieval and Classification Techniques

Cited by 39

Quantum adiabatic algorithm design using reinforcement learning

Lin, J., Lai, Z. Y., & Li, X. (2020) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 39

Multimodal Attention Network for Continuous-Time Emotion Recognition Using Video and EEG Signals

Choi, D. Y., Kim, D.-H., & Song, B. C. (2020) · IEEE Access

Emotion and Mood RecognitionFace and Expression Recognition

Cited by 39

To what extent will blockchain drive the machine economy? Perspectives from a prospective study

Schweizer, A., Knoll, P., Urbach, N., von der Gracht, H. A., & Hardjono, T. (2020) · IEEE Transactions on Engineering Management

Blockchain Technology Applications and SecurityImpact of AI and Big Data on Business and Society

Cited by 39

A Quantitative Approach for Evaluating the Quality of Experience of Smart-Wearables From the Quality of Data and Quality of Information: An End User Perspective

Pal, D., Vanijja, V., Arpnikanondt, C., Zhang, X., & Papasratorn, B. (2019) · IEEE Access

Innovative Human-Technology InteractionImage and Video Quality Assessment

Cited by 39