Check computer science papers: citations, claims and retractions

ProAgent: Building Proactive Cooperative Agents with Large Language Models

Zhang, C., Yang, K., Hu, S., Wang, Z., Li, G., Sun, Y., Zhang, C., Zhang, Z., Liu, A., Zhu, S.-C., et al. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsMulti-Agent Systems and Negotiation

Cited by 88

Training a quantum optimizer

Wecker, D., Hastings, M. B., & Troyer, M. (2016) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 88

"It Felt Like Having a Second Mind": Investigating Human-AI Co-creativity in Prewriting with Large Language Models

Wan, Q., Hu, S., Zhang, Y., Wang, P., Wen, B., & Lu, Z. (2024) · Proceedings of the ACM on Human-Computer Interaction

Innovative Human-Technology InteractionDesign Education and Practice

Cited by 88

Health workers’ knowledge of and attitudes towards computer applications in rural African health facilities

Sukums, F., Mensah, N., Mpembeni, R., Kaltschmidt, J., Haefeli, W. E., & Blank, A. (2014) · Global Health Action

ICT in Developing CommunitiesElectronic Health Records Systems

Cited by 88

A new approach for oil tank detection using deep learning features with control false alarm rate in high-resolution satellite imagery

Zalpour, M., Akbarizadeh, G., & Alaei-Sheini, N. (2020) · International Journal of Remote Sensing

Remote-Sensing Image ClassificationAdvanced Neural Network Applications

Cited by 88

SyncTalkFace: Talking Face Generation with Precise Lip-Syncing via Audio-Lip Memory

Park, S. J., Kim, M., Hong, J., Choi, J., & Ro, Y. M. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence

Generative Adversarial Networks and Image SynthesisSpeech and Audio Processing

Cited by 88

The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study

Tang, Z., Wang, Y., Wang, Q., & Chu, X. (2019) · Proceedings of the Tenth ACM International Conference on Future Energy Systems

Parallel Computing and Optimization TechniquesEnergy Efficiency in Computing

Cited by 88

Designing Heterogeneous LLM Agents for Financial Sentiment Analysis

Xing, F. (2025) · ACM Transactions on Management Information Systems

Sentiment Analysis and Opinion MiningStock Market Forecasting Methods

Cited by 88

A deep learning model integrating mammography and clinical factors facilitates the malignancy prediction of BI-RADS 4 microcalcifications in breast cancer screening

Liu, H., Chen, Y., Zhang, Y., Wang, L., Luo, R., Wu, H., Wu, C., Zhang, H., Tan, W., Yin, H., et al. (2021) · European Radiology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 88

Load Balancing Based Task Scheduling with ACO in Cloud Computing

Gupta, A., & Garg, R. (2017) · 2017 International Conference on Computer and Applications (ICCA)

Cloud Computing and Resource ManagementDistributed and Parallel Computing Systems

Cited by 88

HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark

Li, C., Yu, Z., Fu, Y., Zhang, Y., Zhao, Y., You, H., Yu, Q., Wang, Y., & Lin, Y. C. (2021) · arXiv

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 88

Examining the use of prompts to facilitate self-regulated learning in Massive Open Online Courses

Wong, J., Baars, M., de Koning, B. B., & Paas, F. (2021) · Computers in Human Behavior

Online Learning and AnalyticsInnovative Teaching and Learning Methods

Cited by 88

A generalized back-door criterion

Maathuis, M. H., & Colombo, D. (2015) · The Annals of Statistics

Bayesian Modeling and Causal InferenceAdvanced Causal Inference Techniques

Cited by 88

A fungus spores dataset and a convolutional neural network based approach for fungus detection

Tahir, M. W., Zaidi, N. A., Rao, A. A., Blank, R., Vellekoop, M. J., & Lang, W. (2018) · IEEE Transactions on NanoBioscience

Advanced Neural Network ApplicationsSmart Agriculture and AI

Cited by 88

A multimodal emotion recognition method based on facial expressions and electroencephalography

Tan, Y., Sun, Z., Duan, F., Solé-Casals, J., & Caiafa, C. F. (2021) · Biomedical Signal Processing and Control

Emotion and Mood RecognitionSocial Robot Interaction and HRI

Cited by 88

Counterfactual Explanations for Multivariate Time Series

Ates, E., Aksar, B., Leung, V. J., & Coskun, A. K. (2021) · 2021 International Conference on Applied Artificial Intelligence (ICAPAI)

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 88

An Intelligent System for Video Surveillance in IoT Environments

Rego, A., Canovas, A., Jimenez, J. M., & Lloret, J. (2018) · IEEE Access

Software-Defined Networks and 5GInternet Traffic Analysis and Secure E-voting

Cited by 88

Cross-Topic Learning for Work Prioritization in Systematic Review Creation and Update

Cohen, A. M., Ambert, K., & McDonagh, M. (2009) · Journal of the American Medical Informatics Association

Information Retrieval and Search BehaviorMeta-analysis and systematic reviews

Cited by 88

Joint feature synthesis and embedding: Adversarial cross-modal retrieval revisited

Xu, X., Lin, K., Yang, Y., Hanjalic, A., & Shen, H. T. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 88

A Survey of Confidence Estimation and Calibration in Large Language Models . -

Geng, J., Cai, F., Wang, Y., Koeppl, H., Nakov, P., & Gurevych, I. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 88

GA-mADAM-IIoT: A new lightweight threats detection in the industrial IoT via genetic algorithm with attention mechanism and LSTM on multivariate time series sensor data

Saheed, Y. K., Omole, A. I., & Sabit, M. O. (2025) · Sensors International

Network Security and Intrusion DetectionInternet of Things and AI

Cited by 88

DFDT: An End-to-End DeepFake Detection Framework Using Vision Transformer

Khormali, A., & Yuan, J.-S. (2022) · Applied Sciences

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 88

ICface: Interpretable and Controllable Face Reenactment Using GANs

Tripathy, S., Kannala, J., & Rahtu, E. (2020) · 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 88

Human detection based on deep learning YOLO-v2 for real-time UAV applications

Boudjit, K., & Ramzan, N. (2022) · Journal of Experimental & Theoretical Artificial Intelligence

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 88