Check computer science papers: citations, claims and retractions

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

Neel, S., Roth, A., & Sharifi-Malvajerdi, S. (2020) · arXiv

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 96

Online Model Distillation for Efficient Video Inference

Mullapudi, R. T., Chen, S., Zhang, K., Ramanan, D., & Fatahalian, K. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 96

MeFoRE: QoE based resource estimation at Fog to enhance QoS in IoT

Aazam, M., St-Hilaire, M., Lung, C.-H., & Lambadaris, I. (2016) · 2016 23rd International Conference on Telecommunications (ICT)

IoT and Edge/Fog ComputingCloud Computing and Resource Management

Cited by 96

GLOBEM: Cross-Dataset Generalization of Longitudinal Human Behavior Modeling

Xu, X., Liu, X., Zhang, H., Wang, W., Nepal, S., Sefidgar, Y., Seo, W., Kuehn, K. S., Huckins, J. F., Morris, M. E., et al. (2022) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Emotion and Mood RecognitionContext-Aware Activity Recognition Systems

Cited by 96

Bots, Bias and Big Data: Artificial Intelligence, Algorithmic Bias and Disparate Impact Liability in Hiring Practices

Raub, M. (2018) · Arkansas Law Review

Ethics and Social Impacts of AIAI and HR Technologies

Cited by 96

Please, tell me about yourself: automatic personality assessment using short self-presentations

Batrinca, L. M., Mana, N., Lepri, B., Pianesi, F., & Sebe, N. (2011) · Proceedings of the 13th international conference on multimodal interfaces

Emotion and Mood RecognitionPersonality Traits and Psychology

Cited by 96

Does ChatGPT Help With Introductory Programming?An Experiment of Students Using ChatGPT in CS1

Xue, Y., Chen, H., Bai, G. R., Tairas, R., & Huang, Y. (2024) · Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training

Teaching and Learning ProgrammingArtificial Intelligence in Education

Cited by 96

Embers of autoregression show how large language models are shaped by the problem they are trained to solve

McCoy, R. T., Yao, S., Friedman, D., Hardy, M. D., & Griffiths, T. L. (2024) · Proceedings of the National Academy of Sciences

Topic ModelingNatural Language Processing Techniques

Cited by 96

LogPrompt: Prompt Engineering Towards Zero-Shot and Interpretable Log Analysis

Liu, Y., Tao, S., Meng, W., Yao, F., Zhao, X., & Yang, H. (2024) · Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings

Software System Performance and ReliabilitySoftware Engineering Research

Cited by 96

Collaborative construction of artificial intelligence curriculum in primary schools

Dai, Y., Liu, A., Qin, J., Guo, Y., Jong, M. S., Chai, C., & Lin, Z. (2023) · Journal of Engineering Education

Teaching and Learning ProgrammingEducational Theory and Curriculum Studies

Cited by 96

Semi-Supervised Classification of Network Data Using Very Few Labels

Lin, F., & Cohen, W. W. (2010) · 2010 International Conference on Advances in Social Networks Analysis and Mining

Machine Learning and AlgorithmsAdvanced Graph Neural Networks

Cited by 96

General conditions for quantum adiabatic evolution

Comparat, D. (2009) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications

Cited by 95

MODNet: Motion and Appearance based Moving Object Detection Network for Autonomous Driving

Siam, M., Mahgoub, H., Zahran, M., Yogamani, S., Jagersand, M., & El-Sallab, A. (2018) · 2018 21st International Conference on Intelligent Transportation Systems (ITSC)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 95

On the spatial statistics of optical flow

Roth, S., & Black, M. J. (2005) · Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1

Advanced Vision and ImagingVideo Surveillance and Tracking Methods

Cited by 95

Universal Adversarial Perturbation via Prior Driven Uncertainty Approximation

Liu, H., Ji, R., Li, J., Zhang, B., Gao, Y., Wu, Y., & Huang, F. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 95

Unsolved Problems in ML Safety

Hendrycks, D., Carlini, N., Schulman, J., & Steinhardt, J. (2021) · arXiv

Ethics and Social Impacts of AISafety Systems Engineering in Autonomy

Cited by 95

On the Universality of the Quantum Approximate Optimization Algorithm

Morales, M. E. S., Biamonte, J., & Zimborás, Z. (2019) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 95

EX2: Exploration with Exemplar Models for Deep Reinforcement Learning

Fu, J., Co-Reyes, J. D., & Levine, S. (2017) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 95

Software engineering for machine-learning applications: The road ahead

Khomh, F., Adams, B., Cheng, J., Fokaefs, M., & Antoniol, G. (2018) · IEEE Software

Software Engineering Techniques and PracticesSoftware Engineering Research

Cited by 95

HONEST: Measuring Hurtful Sentence Completion in Language Models

Nozza, D., Bianchi, F., & Hovy, D. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection

Cited by 95

A systematic review of intermediate fusion in multimodal deep learning for biomedical applications

Guarrasi, V., Aksu, F., Caruso, C. M., Di Feola, F., Rofena, A., Ruffini, F., & Soda, P. (2025) · Image and Vision Computing

Multimodal Machine Learning ApplicationsAdvanced Image Fusion Techniques

Cited by 95

The vocal joystick: evaluation of voice-based cursor control techniques

Harada, S., Landay, J. A., Malkin, J., Li, X., & Bilmes, J. A. (2006) · Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility

Gaze Tracking and Assistive TechnologyAssistive Technology in Communication and Mobility

Cited by 95

A Human-Centered Systematic Literature Review of the Computational Approaches for Online Sexual Risk Detection

Razi, A., Kim, S., Alsoubai, A., Stringhini, G., Solorio, T., De Choudhury, M., & Wisniewski, P. J. (2021) · Proceedings of the ACM on Human-Computer Interaction

Hate Speech and Cyberbullying DetectionEthics and Social Impacts of AI

Cited by 95

Audio Deepfake Detection With Self-Supervised WavLM And Multi-Fusion Attentive Classifier

Guo, Y., Huang, H., Chen, X., Zhao, H., & Wang, Y. (2024) · ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 95