Check computer science papers: citations, claims and retractions

Reducing risk posed by synthetic content an overview of technical approaches to digital content transparency

National Institute of Standards and Technology (US) (2024)

Digital Media Forensic DetectionAdvanced Steganography and Watermarking Techniques

Cited by 9

To See or Not to See: Understanding the Tensions of Algorithmic Curation for Visual Arts

Srinivasan, R. (2024) · The 2024 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIArt, Technology, and Culture

Cited by 9

Latent Pattern Sensing: Deepfake Video Detection via Predictive Representation Learning

Ge, S., Lin, F., Li, C., Zhang, D., Tan, J., Wang, W., & Zeng, D. (2021) · ACM Multimedia Asia

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 9

Industrial Big Data Visualization: A Case Study Using Flight Data Recordings to Discover the Factors Affecting the Airplane Fuel Efficiency

Li, M., & Zhou, Q. (2017) · 2017 IEEE Trustcom/BigDataSE/ICESS

Data Visualization and AnalyticsBig Data Technologies and Applications

Cited by 9

Towards a Robust Detection of Language Model-Generated Text: Is ChatGPT that easy to detect?

Antoun, W., Mouilleron, V., Sagot, B., & Seddah, D. (2023) · arXiv

Authorship Attribution and ProfilingAdversarial Robustness in Machine Learning

Cited by 9

Detecting and Understanding Textual Deepfakes in Online Reviews

Kowalczyk, P., Röder, M., Dürr, A., & Thiesse, F. (2022) · Proceedings of the Annual Hawaii International Conference on System Sciences

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 9

A Gaussian Process perspective on Convolutional Neural Networks

Borovykh, A. (2018) · arXiv

Gaussian Processes and Bayesian InferenceNeural Networks and Applications

Cited by 9

Optimizing Large Language Models for Auto-Generation of Programming Quizzes

Kumar, Y., Manikandan, A., Li, J. J., & Morreale, P. (2024) · 2024 IEEE Integrated STEM Education Conference (ISEC)

Teaching and Learning ProgrammingArtificial Intelligence in Education

Cited by 9

Improving Usability Perception of Error-Prone AI Speakers: Elaborated Feedback Mitigates Negative Consequences of Errors

Lee, D., Sah, Y. J., & Lee, S. (2019) · International Journal of Human–Computer Interaction

Speech and dialogue systemsUsability and User Interface Design

Cited by 9

Sparse Meets Dense: A Hybrid Approach to Enhance Scientific Document Retrieval

Mandikal, P., & Mooney, R. (2024) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 9

My Code Is Less Secure with Gen AI: Surveying Developers' Perceptions of the Impact of Code Generation Tools on Security

Kudriavtseva, A., Hotak, N. A., & Gadyatskaya, O. (2025) · Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing

Software Engineering ResearchWeb Application Security Vulnerabilities

Cited by 9

Spontaneous Facial Expression Recognition Based on Feature Point Tracking

He, S., Wang, S., & Lv, Y. (2011) · 2011 Sixth International Conference on Image and Graphics

Emotion and Mood RecognitionFace recognition and analysis

Cited by 9

SecureBERT and LLAMA 2 Empowered Control Area Network Intrusion Detection and Classification

Li, X., & Fu, H. (2023) · arXiv

Network Security and Intrusion DetectionAdversarial Robustness in Machine Learning

Cited by 9

WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment

Tang, H., Key, D., & Ellis, K. (2024) · arXiv

AI-based Problem Solving and PlanningReinforcement Learning in Robotics

Cited by 9

Action chunking as conditional policy compression

Lai, L., Huang, A. Z., & Gershman, S. J. (2022)

AI-based Problem Solving and PlanningMotor Control and Adaptation

Cited by 9

A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms

Abercrombie, G., Benbouzid, D., Giudici, P., Golpayegani, D., Hernandez, J., Noro, P., Pandit, H., Paraschou, E., Pownall, C., Prajapati, J., et al. (2024) · arXiv

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 9

Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning

Fu, R., Liu, J., Chen, X., Nie, Y., & Xiong, W. (2024) · arXiv

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 9

User-Centered Design in Mobile Human-Robot Cooperation: Consideration of Usability and Situation Awareness in GUI Design for Mobile Robots at Assembly Workplaces

Colceriu, C., Theis, S., Brell-Cokcan, S., & Nitsch, V. (2023) · i-com

Usability and User Interface DesignInteractive and Immersive Displays

Cited by 9

NEUROSEC: FPGA-Based Neuromorphic Audio Security

Isik, M., Vishwamith, H., Sur, Y., Inadagbo, K., & Dikmen, I. C. (2024) · arXiv

Physical Unclonable Functions (PUFs) and Hardware SecurityAdversarial Robustness in Machine Learning

Cited by 9

Developing Successful Speakers for an Automatic Speech Recognition System

Danis, C. M. (1989) · Proceedings of the Human Factors Society Annual Meeting

Speech Recognition and SynthesisSpeech and dialogue systems

Cited by 9

Incorporating Computational Thinking Into Virtual Laboratories to Enhance Learning Motivation, Engagement, and Higher‐Order Thinking Skills

Wu, T., Sarwono, E., & Huang, Y. (2025) · Journal of Computer Assisted Learning

Teaching and Learning ProgrammingExperimental Learning in Engineering

Cited by 9

Investigating flicker noise effect on randomness of CMOS ring oscillator based true random number generators

Guler, U., Pusane, A. E., & Dundar, G. (2014) · 2014 International Conference on Information Science, Electronics and Electrical Engineering

Physical Unclonable Functions (PUFs) and Hardware SecurityAnalog and Mixed-Signal Circuit Design

Cited by 9

Nonparametric Decoding for Generative Retrieval

Lee, H., Kim, J., Chang, H., Oh, H., Yang, S., Karpukhin, V., Lu, Y., & Seo, M. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Information Retrieval and Search BehaviorTopic Modeling

Cited by 9

Clinical trial recommendations using Semantics-Based inductive inference and knowledge graph embeddings

Devarakonda, M. V., Mohanty, S., Sunkishala, R. R., Mallampalli, N., & Liu, X. (2024) · Journal of Biomedical Informatics

Recommender Systems and TechniquesAdvanced Graph Neural Networks

Cited by 9