Check computer science papers: citations, claims and retractions

Deepfake-Driven Social Engineering: Threats, Detection Techniques, and Defensive Strategies in Corporate Environments

Pedersen, K. T., Pepke, L., Stærmose, T., Papaioannou, M., Choudhary, G., & Dragoni, N. (2025) · Journal of Cybersecurity and Privacy

Information and Cyber SecuritySpam and Phishing Detection

Cited by 15

Investigating the Operational Complexity of Digital Workflows Based on Human Cognitive Aspects

Horváth, I., & Berki, B. (2023) · Electronics

Interactive and Immersive DisplaysUsability and User Interface Design

Cited by 15

High-performance repetition cat code using fast noisy operations

Régent, F.-M. L., Berdou, C., Leghtas, Z., Guillaud, J., & Mirrahimi, M. (2023) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 15

Exploring Designers’ Perceptions and Practices of Collaborating with Generative AI as a Co-creative Agent in a Multi-stakeholder Design Process: Take the Domain of Avatar Design as an Example

He, Q., Zheng, W., Bao, H., Chen, R., & Tong, X. (2023) · Proceedings of the Eleventh International Symposium of Chinese CHI

Digital Media and Visual ArtDesign Education and Practice

Cited by 15

Prometheus: Inducing Fine-grained Evaluation Capability in Language Models

Kim, S., Shin, J., Cho, Y., Jang, J., Longpre, S., Lee, H., Yun, S., Shin, S., Kim, S., Thorne, J., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 15

Towards a Reflection in Creative Experience Questionnaire

Ford, C., & Bryan-Kinns, N. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionCreativity in Education and Neuroscience

Cited by 15

Learning Lexico-Functional Patterns for First-Person Affect

Reed, L., Wu, J., Oraby, S., Anand, P., & Walker, M. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 15

Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training data

Mitchell, J. R., Kamnitsas, K., Singleton, K. W., Whitmire, S. A., Clark-Swanson, K. R., Ranjbar, S., Rickertsen, C. R., Johnston, S. K., Egan, K. M., Rollison, D. E., et al. (2020) · Journal of Medical Imaging

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 15

Visual Question Generation from Radiology Images

Sarrouti, M., Ben Abacha, A., & Demner-Fushman, D. (2020) · Proceedings of the First Workshop on Advances in Language and Vision Research

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 15

Kimi K2: Open Agentic Intelligence

Kimi Team, Bai, Y., Bao, Y., Charles, Y., Chen, C., Chen, G., Chen, H., Chen, H., Chen, J., Chen, N., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 15

Edge-MultiAI: Multi-Tenancy of Latency-Sensitive Deep Learning Applications on Edge

Zobaed, S., Mokhtari, A., Champati, J. P., Kourouma, M., & Salehi, M. A. (2022) · 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC)

IoT and Edge/Fog ComputingAdvanced Neural Network Applications

Cited by 15

SpeechPrompt v2: Prompt Tuning for Speech Classification Tasks

Chang, K.-W., Wang, Y.-K., Shen, H., Kang, I.-T., Tseng, W.-C., Li, S.-W., & Lee, H.-Y. (2023) · arXiv

Speech Recognition and SynthesisDomain Adaptation and Few-Shot Learning

Cited by 15

In a dirty virtual room: Exposure to an unpleasant odor increases the senses of presence, reality, and realism

Baus, O., Bouchard, S., Nolet, K., & Berthiaume, M. (2022) · Cogent Psychology

Virtual Reality Applications and ImpactsMultisensory perception and integration

Cited by 15

AutoML Strategy Based on Grammatical Evolution: A Case Study about Knowledge Discovery from Text

Estevez-Velarde, S., Gutiérrez, Y., Montoyo, A., & Almeida-Cruz, Y. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Machine Learning and Data ClassificationEvolutionary Algorithms and Applications

Cited by 15

A Hybrid Multi-Agent Conversational Recommender System with LLM and Search Engine in E-commerce

Nie, G., Zhi, R., Yan, X., Du, Y., Zhang, X., Chen, J., Zhou, M., Chen, H., Li, T., Cheng, Z., et al. (2024) · 18th ACM Conference on Recommender Systems

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 15

Can Alexa be your Therapist?: How Back-Channeling Transforms Smart-Speakers to be Active Listeners

Motalebi, N., Cho, E., Sundar, S. S., & Abdullah, S. (2019) · Companion Publication of the 2019 Conference on Computer Supported Cooperative Work and Social Computing

Speech and dialogue systemsSocial Robot Interaction and HRI

Cited by 15

Automated Identification of Eviction Status From Electronic Health Record Notes

Yao, Z., Tsai, J., Liu, W., Levy, D. A., Druhl, E., Reisman, J. I., & Yu, H. (2023) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareMental Health via Writing

Cited by 15

PAIR PROGRAMMING AS A TEAM BASED LEARNING ACTIVITY: A REVIEW OF RESEARCH

Faja, S. (2011) · Issues In Information Systems

Teaching and Learning ProgrammingProblem and Project Based Learning

Cited by 15

A designerly approach as a foundation for school children's computational thinking skills while developing digital games

Brooks, E., & Sjöberg, J. (2020) · Proceedings of the Interaction Design and Children Conference

Teaching and Learning ProgrammingDesign Education and Practice

Cited by 15

Optimal design of fractional delay filters

Nagahara, M., & Yamamoto, Y. (2004) · 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475)

Digital Filter Design and ImplementationAdvanced Adaptive Filtering Techniques

Cited by 15

Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System

Liu, Y., Zhang, C., Yan, X., Chang, Y., & Yu, P. S. (2019) · Proceedings of the 28th ACM International Conference on Information and Knowledge Management

Topic ModelingInformation Retrieval and Search Behavior

Cited by 15

Fusing Multimodal Video Data for Detecting Moving Objects/Targets in Challenging Indoor and Outdoor Scenes

Kandylakis, Z., Vasili, K., & Karantzalos, K. (2019) · Remote Sensing

Video Surveillance and Tracking MethodsAdvanced Image Fusion Techniques

Cited by 15

Hold me tight! Influence of discriminative features on deep network boundaries

Ortiz-Jimenez, G., Modas, A., Moosavi-Dezfooli, S.-M., & Frossard, P. (2020) · arXiv

Adversarial Robustness in Machine LearningExplainable Artificial Intelligence (XAI)

Cited by 15

Towards Personalised Mood Prediction and Explanation for Depression from Biophysical Data

Chatterjee, S., Mishra, J., Sundram, F., & Roop, P. (2023) · Sensors

Emotion and Mood RecognitionDigital Mental Health Interventions

Cited by 15