Check computer science papers: citations, claims and retractions

Deep Speech Synthesis from Articulatory Representations

Wu, P., Watanabe, S., Goldstein, L., Black, A. W., & Anumanchipalli, G. K. (2022) · Interspeech 2022

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 22

Do Language Embeddings capture Scales?

Zhang, X., Ramachandran, D., Tenney, I., Elazar, Y., & Roth, D. (2020) · Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP

Topic ModelingMultimodal Machine Learning Applications

Cited by 22

KSwSVR: A New Load Forecasting Method for Efficient Resources Provisioning in Cloud

Hu, R., Jiang, J., Liu, G., & Wang, L. (2013) · 2013 IEEE International Conference on Services Computing

Cloud Computing and Resource ManagementEnergy Efficiency in Computing

Cited by 22

EPNS: Efficient Privacy-Preserving Intelligent Traffic Navigation From Multiparty Delegated Computation in Cloud-Assisted VANETs

Zhou, J., Chen, S., Choo, K.-K. R., Cao, Z., & Dong, X. (2021) · IEEE Transactions on Mobile Computing

Cryptography and Data SecurityVehicular Ad Hoc Networks (VANETs)

Cited by 22

BDPS: An Efficient Spark-Based Big Data Processing Scheme for Cloud Fog-IoT Orchestration

Hossen, R., Whaiduzzaman, M., Uddin, M. N., Islam, M. J., Faruqui, N., Barros, A., Sookhak, M., & Mahi, M. J. N. (2021) · Information

IoT and Edge/Fog ComputingCloud Computing and Resource Management

Cited by 22

Provocative testing for the assessment of the electromagnetic interference of RFID and NFC readers on implantable pacemaker

Mattei, E., Lucano, E., Censi, F., Triventi, M., & Calcagnini, G. (2016) · IEEE Transactions on Electromagnetic Compatibility

RFID technology advancementsCardiac pacing and defibrillation studies

Cited by 22

Artificial Intelligence in the Diagnosis of Colorectal Cancer: A Literature Review

Uchikov, P., Khalid, U., Kraev, K., Hristov, B., Kraeva, M., Tenchev, T., Chakarov, D., Sandeva, M., Dragusheva, S., Taneva, D., et al. (2024) · Diagnostics

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 22

On-device Federated Learning with Flower

Mathur, A., Beutel, D. J., de Gusmão, P. P. B., Fernandez-Marques, J., Topal, T., Qiu, X., Parcollet, T., Gao, Y., & Lane, N. D. (2021) · arXiv

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 22

Natural interaction in virtual reality: impact on the cognitive load

Galais, T., Delmas, A., & Alonso, R. (2019) · Adjunct Proceedings of the 31st Conference on l'Interaction Homme-Machine

Interactive and Immersive DisplaysHand Gesture Recognition Systems

Cited by 22

Backdoor Attacks on Federated Meta-Learning

Chen, C.-L., Golubchik, L., & Paolieri, M. (2020) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 22

Deep sequential models for suicidal ideation from multiple source data

Peis, I., Olmos, P. M., Vera-Varela, C., Barrigon, M. L., Courtet, P., Baca-Garcia, E., & Artes-Rodriguez, A. (2019) · IEEE Journal of Biomedical and Health Informatics

Machine Learning in HealthcareMental Health via Writing

Cited by 22

Rating AI systems for bias to promote trustable applications

Srivastava, B., & Rossi, F. (2019) · IBM Journal of Research and Development

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 22

Algorithmic Governance: Experimental Evidence on Citizens' and Public Administrators' Legitimacy Perceptions of Automated Decision‐Making

Hillo, J., Vento, I., & Erkkilä, T. (2026) · Public Administration

Ethics and Social Impacts of AIE-Government and Public Services

Cited by 22

An innovative random-forest-based model to assess the health impacts of regular commuting using non-invasive wearable sensors

Sharif, M. S., Raj Theeng Tamang, M., Fu, C. H. Y., Baker, A., Alzahrani, A. I., & Alalwan, N. (2023) · Sensors

Emotion and Mood RecognitionNon-Invasive Vital Sign Monitoring

Cited by 22

A Survey on the Optimization of Large Language Model-based Agents

Du, S., Zhao, J., Shi, J., Xie, Z., Jiang, X., Bai, Y., & He, L. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 22

Social Engineering Techniques, Risks, and Controls

Hinson, G. (2008) · EDPACS

Information and Cyber SecuritySpam and Phishing Detection

Cited by 22

Benchmark Data Contamination of Large Language Models: A Survey

Xu, C., Guan, S., Greene, D., & Kechadi, M.-T. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 22

No value restriction is needed for algebraic effects and handlers

KAMMAR, O., & PRETNAR, M. (2017) · Journal of Functional Programming

Logic, programming, and type systemsAdvanced Algebra and Logic

Cited by 22

Explainable AI based Interventions for Pre-season Decision Making in Fashion Retail

Sajja, S., Aggarwal, N., Mukherjee, S., Manglik, K., Dwivedi, S., & Raykar, V. (2021) · Proceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD)

Explainable Artificial Intelligence (XAI)Cultural and Historical Studies

Cited by 22

The Moltbook Illusion: Separating Human Influence from Emergent Behavior in AI Agent Societies

Li, N. (2026) · arXiv

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 22

The Parallelism Tradeoff: Limitations of Log-Precision Transformers

Merrill, W., & Sabharwal, A. (2023) · Transactions of the Association for Computational Linguistics

semigroups and automata theoryComplexity and Algorithms in Graphs

Cited by 22

The Productivity Effects of Generative AI: Evidence from a Field Experiment with GitHub Copilot

Cui, K. Z., Demirer, M., Jaffe, S., Musolff, L., Peng, S., & Salz, T. (2024) · An MIT Exploration of Generative AI

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 22

Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Gupta, A., Xu, J., Upadhyay, S., Yang, D., & Faruqui, M. (2021) · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

Topic ModelingNatural Language Processing Techniques

Cited by 22

DEMETR: Diagnosing Evaluation Metrics for Translation

Karpinska, M., Raj, N., Thai, K., Song, Y., Gupta, A., & Iyyer, M. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 22