Check computer science papers: citations, claims and retractions

E-VAT: An Asymmetric End-to-End Approach to Visual Active Exploration and Tracking

Dionigi, A., Devo, A., Guiducci, L., & Costante, G. (2022) · IEEE Robotics and Automation Letters

Reinforcement Learning in RoboticsVideo Surveillance and Tracking Methods

Cited by 28

Deepfake detection across image, video, and audio: a comprehensive survey with empirical evaluation of generalization and robustness

Nguyen-Le, H.-H., Tran, V.-T., Nguyen, D.-T., & Le-Khac, N.-A. (2026) · Artificial Intelligence Review

Digital Media Forensic DetectionBiometric Identification and Security

Cited by 28

Certifying LLM Safety against Adversarial Prompting

Kumar, A., Agarwal, C., Srinivas, S., Li, A. J., Feizi, S., & Lakkaraju, H. (2023) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 28

HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

Mazeika, M., Phan, L., Yin, X., Zou, A., Wang, Z., Mu, N., Sakhaee, E., Li, N., Basart, S., Li, B., et al. (2024) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 28

An Anomaly Detection Method Based on Multiple LSTM-Autoencoder Models for In-Vehicle Network

Kim, T., Kim, J., & You, I. (2023) · Electronics

Network Security and Intrusion DetectionAdversarial Robustness in Machine Learning

Cited by 28

Cross-dataset deep transfer learning for activity recognition

Gjoreski, M., Kalabakov, S., Luštrek, M., Gams, M., & Gjoreski, H. (2019) · Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers

Domain Adaptation and Few-Shot LearningContext-Aware Activity Recognition Systems

Cited by 28

Skeleton-Based Fall Detection with Multiple Inertial Sensors Using Spatial-Temporal Graph Convolutional Networks

Yan, J., Wang, X., Shi, J., & Hu, S. (2023) · Sensors

Context-Aware Activity Recognition SystemsBalance, Gait, and Falls Prevention

Cited by 28

One label is all you need: Interpretable AI-enhanced histopathology for oncology

Tavolara, T. E., Su, Z., Gurcan, M. N., & Niazi, M. K. K. (2023) · Seminars in Cancer Biology

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 28

Audio-Visual Face Reenactment

Agarwal, M., Mukhopadhyay, R., Namboodiri, V., & Jawahar, C. V. (2023) · 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 28

Curiosity Notebook: A Platform for Learning by Teaching Conversational Agents

Law, E., Baghaei Ravari, P., Chhibber, N., Kulic, D., Lin, S., Pantasdo, K. D., Ceha, J., Suh, S., & Dillen, N. (2020) · Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems

Intelligent Tutoring Systems and Adaptive LearningSocial Robot Interaction and HRI

Cited by 28

Factoring with n+2 clean qubits and n-1 dirty qubits

Gidney, C. (2017) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 28

SSFE-Net: Self-Supervised Feature Enhancement for Ultra-Fine-Grained Few-Shot Class Incremental Learning

Pan, Z., Yu, X., Zhang, M., & Gao, Y. (2023) · 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 28

Taking AI Welfare Seriously

Long, R., Sebo, J., Butlin, P., Finlinson, K., Fish, K., Harding, J., Pfau, J., Sims, T., Birch, J., & Chalmers, D. (2024) · arXiv

Ethics and Social Impacts of AILiterary and Philosophical Studies

Cited by 27

An Enhanced Neural Word Embedding Model for Transfer Learning

Kowsher, M., Sobuj, M. S. I., Shahriar, M. F., Prottasha, N. J., Arefin, M. S., Dhar, P. K., & Koshiba, T. (2022) · Applied Sciences

Topic ModelingNatural Language Processing Techniques

Cited by 27

Qwen3-VL Technical Report

Bai, S., Cai, Y., Chen, R., Chen, K., Chen, X., Cheng, Z., Deng, L., Ding, W., Gao, C., Ge, C., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 27

A Generative Artificial Intelligence (AI)-Based Human-Computer Collaborative Programming Learning Method to Improve Computational Thinking, Learning Attitudes, and Learning Achievement

Zhao, G., Yang, L., Hu, B., & Wang, J. (2025) · Journal of Educational Computing Research

Teaching and Learning ProgrammingArtificial Intelligence in Education

Cited by 27

A problem-based approach to the advancement of heuristics for socio-technical evaluation

Herrmann, T., Jahnke, I., & Nolte, A. (2022) · Behaviour & Information Technology

Usability and User Interface DesignInformation Systems Theories and Implementation

Cited by 27

Towards Designing Conversational Agents for Pair Programming: Accounting for Creativity Strategies and Conversational Styles

Kuttal, S. K., Myers, J., Gurka, S., Magar, D., Piorkowski, D., & Bellamy, R. (2020) · 2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

Teaching and Learning ProgrammingSoftware Engineering Techniques and Practices

Cited by 27

Robust, low-cost, auditable random number generation for embedded system security

Lampert, B., Wahby, R. S., Leonard, S., & Levis, P. (2016) · Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems CD-ROM

Physical Unclonable Functions (PUFs) and Hardware SecurityCryptographic Implementations and Security

Cited by 27

Bayesian packet loss detection for TCP

I'onseca, N., & Crovella, M. (2005) · Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies.

Network Traffic and Congestion ControlWireless Networks and Protocols

Cited by 27

Triggering triggers and burying barriers to customizing software

Banovic, N., Chevalier, F., Grossman, T., & Fitzmaurice, G. (2012) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignSoftware Engineering Techniques and Practices

Cited by 27

Timing analysis of reliable real-time communication in CAN networks

Pinho, L. M., & Vasques, F. (2002) · Proceedings 13th Euromicro Conference on Real-Time Systems

Real-Time Systems SchedulingNetwork Time Synchronization Technologies

Cited by 27

xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token

Cheng, X., Wang, X., Zhang, X., Ge, T., Chen, S.-Q., Wei, F., Zhang, H., & Zhao, D. (2024) · Advances in Neural Information Processing Systems 37

Topic ModelingInformation Retrieval and Search Behavior

Cited by 27

Deep Active Inference for Partially Observable MDPs

van der Himst, O., & Lanillos, P. (2020) · arXiv

Reinforcement Learning in RoboticsEmbodied and Extended Cognition

Cited by 27