Check computer science papers: citations, claims and retractions

Assessing the State of Self-Supervised Human Activity Recognition Using Wearables

Haresamudram, H., Essa, I., & Plötz, T. (2022) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Context-Aware Activity Recognition SystemsDomain Adaptation and Few-Shot Learning

Cited by 107

Hybrid approach for detection of malicious profiles in twitter

Sahoo, S. R., & Gupta, B. B. (2019) · Computers & Electrical Engineering

Spam and Phishing DetectionHate Speech and Cyberbullying Detection

Cited by 107

Artificial intelligence for political decision-making in the European Union: Effects on citizens’ perceptions of input, throughput, and output legitimacy

Starke, C., & Lünich, M. (2020) · Data & Policy

Ethics and Social Impacts of AIEuropean Union Policy and Governance

Cited by 107

Fairness in package-to-group recommendations

Serbos, D., Qi, S., Mamoulis, N., Pitoura, E., & Tsaparas, P. (2017) · Proceedings of the 26th International Conference on World Wide Web

Recommender Systems and TechniquesGame Theory and Voting Systems

Cited by 107

A design methodology for reliable software systems

Liskov, B. H. (1972) · Proceedings of the December 5-7, 1972, fall joint computer conference, part I on - AFIPS '72 (Fall, part I)

Software Reliability and Analysis ResearchDistributed systems and fault tolerance

Cited by 107

Continuous Symmetries and Approximate Quantum Error Correction

Faist, P., Nezami, S., Albert, V. V., Salton, G., Pastawski, F., Hayden, P., & Preskill, J. (2020) · Physical Review X

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 107

Exiting the Cleanroom: On Ecological Validity and Ubiquitous Computing

Carter, S., Mankoff, J., Klemmer, S. R., & Matthews, T. (2008) · Human–Computer Interaction

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 107

How deep neural networks can improve emotion recognition on video data

Khorrami, P., Le Paine, T., Brady, K., Dagli, C., & Huang, T. S. (2016) · 2016 IEEE International Conference on Image Processing (ICIP)

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 107

Virtual reality for pain management in cardiac surgery

Mosso-Vázquez, J. L., Gao, K., Wiederhold, B. K., & Wiederhold, M. D. (2014) · Cyberpsychology, Behavior, and Social Networking

Virtual Reality Applications and ImpactsPediatric Pain Management Techniques

Cited by 107

Blind Hyperspectral Unmixing Using Autoencoders: A Critical Comparison

Palsson, B., Sveinsson, J. R., & Ulfarsson, M. O. (2022) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Remote-Sensing Image ClassificationGeochemistry and Geologic Mapping

Cited by 107

Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)

Jiang, L., Chai, Y., Li, M., Liu, M., Fok, R., Dziri, N., Tsvetkov, Y., Sap, M., Albalak, A., & Choi, Y. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 107

Attend and Discriminate: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors

Abedin, A., Ehsanpour, M., Shi, Q., Rezatofighi, H., & Ranasinghe, D. C. (2021) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Context-Aware Activity Recognition SystemsGait Recognition and Analysis

Cited by 107

DecodingTrust: A comprehensive assessment of trustworthiness in GPT models

Wang, B., Chen, W., Pei, H., Xie, C., Kang, M., Zhang, C., Xu, C., Xiong, Z., Dutta, R., Schaeffer, R., et al. (2023) · Advances in Neural Information Processing Systems 36

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 107

Generality in artificial intelligence

McCarthy, J. (2007) · ACM Turing award lectures

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 107

Spreadsheet Errors: What We Know. What We Think We Can Do

Panko, R. R. (2008) · arXiv

Spreadsheets and End-User ComputingSoftware Engineering Research

Cited by 107

Assessing the State of Self-Supervised Human Activity Recognition using Wearables

Haresamudram, H., Essa, I., & Plötz, T. (2022) · arXiv

Context-Aware Activity Recognition SystemsDomain Adaptation and Few-Shot Learning

Cited by 107

CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility

Xu, G., Liu, J., Yan, M., Xu, H., Si, J., Zhou, Z., Yi, P., Gao, X., Sang, J., Zhang, R., et al. (2023) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 107

MelNet: a generative model for audio in the frequency domain

Vasquez, S., & Lewis, M. (2019) · arXiv

Speech Recognition and SynthesisMusic and Audio Processing

Cited by 107

Measuring Analytic Gradients of General Quantum Evolution with the Stochastic Parameter Shift Rule

Banchi, L., & Crooks, G. E. (2020) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 107

The Biometric Assemblage: Surveillance, Experimentation, Profit, and the Measuring of Refugee Bodies

Madianou, M. (2019) · Television & New Media

Ethics and Social Impacts of AIMigration and Exile Studies

Cited by 107

Do LLMs write like humans? Variation in grammatical and rhetorical styles

Reinhart, A., Markey, B., Laudenbach, M., Pantusen, K., Yurko, R., Weinberg, G., & Brown, D. W. (2025) · Proceedings of the National Academy of Sciences

Authorship Attribution and ProfilingNatural Language Processing Techniques

Cited by 107

TALL: Thumbnail Layout for Deepfake Video Detection

Xu, Y., Liang, J., Jia, G., Yang, Z., Zhang, Y., & He, R. (2023) · arXiv

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 107

Artificial intelligence in the information ecosystem: Affordances for everyday information seeking

Hirvonen, N., Jylhä, V., Lao, Y., & Larsson, S. (2024) · Journal of the Association for Information Science and Technology

Information Retrieval and Search BehaviorInformation Science and Libraries

Cited by 107

Why does surprisal from larger transformer-based language models provide a poorer fit to human reading times?

Oh, B.-D., & Schuler, W. (2023) · Transactions of the Association for Computational Linguistics

Natural Language Processing TechniquesTopic Modeling

Cited by 107