Check computer science papers: citations, claims and retractions

The Off-Switch Game

Hadfield-Menell, D., Dragan, A., Abbeel, P., & Russell, S. (2016) · arXiv

Ethics and Social Impacts of AIPsychiatry, Mental Health, Neuroscience

Cited by 119

Measuring Association Between Labels and Free-Text Rationales

Wiegreffe, S., Marasović, A., & Smith, N. A. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 119

CHESS: Contextual Harnessing for Efficient SQL Synthesis

Talaei, S., Pourreza, M., Chang, Y.-C., Mirhoseini, A., & Saberi, A. (2024) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 119

A comprehensive survey on semantic interoperability for Internet of Things: State‐of‐the‐art and research challenges

Rahman, H., & Hussain, M. I. (2020) · Transactions on Emerging Telecommunications Technologies

Semantic Web and OntologiesIoT and Edge/Fog Computing

Cited by 119

Hidden Backdoors in Human-Centric Language Models

Li, S., Liu, H., Dong, T., Zhao, B. Z. H., Xue, M., Zhu, H., & Lu, J. (2021) · Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 119

Learning to diagnose cirrhosis with liver capsule guided ultrasound image classification

Liu, X., Song, J., Wang, S., Zhao, J., & Chen, Y. (2017) · Sensors

Medical Image Segmentation TechniquesRadiomics and Machine Learning in Medical Imaging

Cited by 119

Comparative review of the blockchain consensus algorithm between proof of stake (pos) and delegated proof of stake (dpos)

Skh Saad, S. M., & Raja Mohd Radzi, R. Z. (2020) · International Journal of Innovative Computing

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 119

LSTM time and frequency recurrence for automatic speech recognition

Li, J., Mohamed, A., Zweig, G., & Gong, Y. (2015) · 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 119

Dislocated accountabilities in the “AI supply chain”: Modularity and developers’ notions of responsibility

Widder, D. G., & Nafus, D. (2023) · Big Data & Society

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 119

AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Guo, Y., Yang, C., Rao, A., Liang, Z., Wang, Y., Qiao, Y., Agrawala, M., Lin, D., & Dai, B. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 119

Mid-circuit correction of correlated phase errors using an array of spectator qubits

Singh, K., Bradley, C. E., Anand, S., Ramesh, V., White, R., & Bernien, H. (2023) · Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 119

AI: the future of humanity

Rawas, S. (2024) · Discover Artificial Intelligence

Artificial Intelligence ApplicationsEthics and Social Impacts of AI

Cited by 119

A Survey of Deep Anomaly Detection in Multivariate Time Series: Taxonomy, Applications, and Directions

Wang, F., Jiang, Y., Zhang, R., Wei, A., Xie, J., & Pang, X. (2025) · Sensors

Anomaly Detection Techniques and ApplicationsTime Series Analysis and Forecasting

Cited by 119

Distributed Consensus on Robot Networks for Dynamically Merging Feature-Based Maps

Aragues, R., Cortes, J., & Sagues, C. (2012) · IEEE Transactions on Robotics

Robotics and Sensor-Based LocalizationDistributed Control Multi-Agent Systems

Cited by 119

Wearable technologies for active living and rehabilitation: Current research challenges and future opportunities

Rodgers, M. M., Alon, G., Pai, V. M., & Conroy, R. S. (2019) · Journal of Rehabilitation and Assistive Technologies Engineering

Context-Aware Activity Recognition SystemsStroke Rehabilitation and Recovery

Cited by 119

Deep learning in biomedical data science

Baldi, P. (2018) · Annual Review of Biomedical Data Science

Machine Learning in HealthcareMachine Learning in Bioinformatics

Cited by 119

Multiple kernel learning for emotion recognition in the wild

Sikka, K., Dykstra, K., Sathyanarayana, S., Littlewort, G., & Bartlett, M. (2013) · Proceedings of the 15th ACM on International conference on multimodal interaction

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 119

Discriminative utterance verification for connected digits recognition

Rahim, M. G., Lee, C.-H., & Juang, B.-H. (1997) · IEEE Transactions on Speech and Audio Processing

Speech Recognition and SynthesisSpeech and dialogue systems

Cited by 119

Nerdy Money: Bitcoin, the Private Digital Currency, and the Case Against Its Regulation

Kaplanov, N. (2012) · SSRN Electronic Journal

Blockchain Technology Applications and SecurityLegal and Constitutional Studies

Cited by 119

Diagnostic Performance of Deep Learning Algorithms Applied to Three Common Diagnoses in Dermatopathology

Olsen, T. G., Jackson, B. H., Feeser, T. A., Kent, M. N., Moad, J. C., Krishnamurthy, S., Lunsford, D. D., & Soans, R. E. (2018) · Journal of Pathology Informatics

AI in cancer detectionCutaneous Melanoma Detection and Management

Cited by 119

My Mobile Music: An Adaptive Personalization System for Digital Audio Players

Chung, T. S., Rust, R. T., & Wedel, M. (2009) · Marketing Science

Recommender Systems and TechniquesAdvanced Bandit Algorithms Research

Cited by 119

Expressibility of the alternating layered ansatz for quantum computation

Nakaji, K., & Yamamoto, N. (2021) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 119

Trust in AutoML: exploring information needs for establishing trust in automated machine learning systems

Drozdal, J., Weisz, J., Wang, D., Dass, G., Yao, B., Zhao, C., Muller, M., Ju, L., & Su, H. (2020) · Proceedings of the 25th International Conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)Human-Automation Interaction and Safety

Cited by 119

GANterfactual—Counterfactual Explanations for Medical Non-experts Using Generative Adversarial Learning

Mertes, S., Huber, T., Weitz, K., Heimerl, A., & André, E. (2022) · Frontiers in Artificial Intelligence

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

Cited by 119