Check computer science papers: citations, claims and retractions

On the Binding Problem in Artificial Neural Networks

Greff, K., van Steenkiste, S., & Schmidhuber, J. (2020) · arXiv

Neural Networks and ApplicationsPsychiatry, Mental Health, Neuroscience

Cited by 102

FinBen: A Holistic Financial Benchmark for Large Language Models

Xie, Q., Han, W., Chen, Z., Xiang, R., Zhang, X., He, Y., Xiao, M., Li, D., Dai, Y., Feng, D., et al. (2024) · Advances in Neural Information Processing Systems 37

Topic ModelingFinTech, Crowdfunding, Digital Finance

Cited by 102

Learning and Adaptation in Cognitive Radios Using Neural Networks

Baldo, N., & Zorzi, M. (2008) · 2008 5th IEEE Consumer Communications and Networking Conference

Cognitive Radio Networks and Spectrum SensingWireless Signal Modulation Classification

Cited by 102

Object Instance Segmentation and Fine-Grained Localization Using Hypercolumns

Hariharan, B., Arbelaez, P., Girshick, R., & Malik, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 102

Human-AI coevolution

Pedreschi, D., Pappalardo, L., Ferragina, E., Baeza-Yates, R., Barabási, A.-L., Dignum, F., Dignum, V., Eliassi-Rad, T., Giannotti, F., Kertész, J., et al. (2025) · Artificial Intelligence

Ethics and Social Impacts of AIRecommender Systems and Techniques

Cited by 102

"How advertiser-friendly is my video?": YouTuber's Socioeconomic Interactions with Algorithmic Content Moderation

Ma, R., & Kou, Y. (2021) · Proceedings of the ACM on Human-Computer Interaction

Ethics and Social Impacts of AIDigital Economy and Work Transformation

Cited by 102

Using BERT to Extract Topic-Independent Sentiment Features for Social Media Bot Detection

Heidari, M., & Jones, J. H. (2020) · 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 102

Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research

Wazzan, M., Algazzawi, D., Bamasaq, O., Albeshri, A., & Cheng, L. (2021) · Applied Sciences

Network Security and Intrusion DetectionSpam and Phishing Detection

Cited by 102

Identity-Preserving Talking Face Generation with Landmark and Appearance Priors

Zhong, W., Fang, C., Cai, Y., Wei, P., Zhao, G., Lin, L., & Li, G. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 102

Residual Mobilities: Infrastructural Displacement and Post-Colonial Computing in Bangladesh

Ahmed, S. I., Mim, N. J., & Jackson, S. J. (2015) · Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

ICT in Developing CommunitiesInnovative Human-Technology Interaction

Cited by 102

A General, Abstract Model of Incremental Dialogue Processing

Schlangen, D., & Skantze, G. (2011) · Dialogue & Discourse

Speech and dialogue systemsNatural Language Processing Techniques

Cited by 102

Entanglement-Assisted Quantum Turbo Codes

Wilde, M. M., Hsieh, M.-H., & Babar, Z. (2014) · IEEE Transactions on Information Theory

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 102

Adoption of artificial intelligence: a TOP framework-based checklist for digital leaders

Tursunbayeva, A., & Chalutz-Ben Gal, H. (2024) · Business Horizons

Artificial Intelligence ApplicationsCorporate Management and Leadership

Cited by 102

Adversarial objects against lidar-based autonomous driving systems

Cao, Y., Xiao, C., Yang, D., Fang, J., Yang, R., Liu, M., & Li, B. (2019) · arXiv

Adversarial Robustness in Machine LearningAutonomous Vehicle Technology and Safety

Cited by 102

Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning

Sun, J., Chen, T., Giannakis, G. B., Yang, Q., & Yang, Z. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 102

P2P-NET: bidirectional point displacement net for shape transform

Yin, K., Huang, H., Cohen-Or, D., & Zhang, H. (2018) · ACM Transactions on Graphics

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 102

Seeing, Listening, Remembering, and Reasoning: A Multimodal Agent with Long-Term Memory

Long, L., He, Y., Ye, W., Pan, Y., Lin, Y., Li, H., Zhao, J., & Li, W. (2025) · arXiv

Multimodal Machine Learning ApplicationsSpeech and dialogue systems

Cited by 102

The Last Mile: Where Artificial Intelligence Meets Reality

Coiera, E. (2019) · Journal of Medical Internet Research

Artificial Intelligence ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 102

Assessing the Extent and Types of Hate Speech in Fringe Communities: A Case Study of Alt-Right Communities on 8chan, 4chan, and Reddit

Rieger, D., Kümpel, A. S., Wich, M., Kiening, T., & Groh, G. (2021) · Social Media + Society

Hate Speech and Cyberbullying DetectionPopulism, Right-Wing Movements

Cited by 102

A flexible sampling-rate conversion method

Smith, J., & Gossett, P. (2005) · ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing

Digital Filter Design and ImplementationAnalog and Mixed-Signal Circuit Design

Cited by 102

Forensics and Analysis of Deepfake Videos

Jafar, M. T., Ababneh, M., Al-Zoube, M., & Elhassan, A. (2020) · 2020 11th International Conference on Information and Communication Systems (ICICS)

Digital Media Forensic DetectionMisinformation and Its Impacts

Cited by 102

Results of the WMT15 Metrics Shared Task

Stanojević, M., Kamran, A., Koehn, P., & Bojar, O. (2015) · Proceedings of the Tenth Workshop on Statistical Machine Translation

Natural Language Processing TechniquesTopic Modeling

Cited by 102

Large Language Models versus Natural Language Understanding and Generation

Karanikolas, N., Manga, E., Samaridi, N., Tousidou, E., & Vassilakopoulos, M. (2023) · Proceedings of the 27th Pan-Hellenic Conference on Progress in Computing and Informatics

Natural Language Processing TechniquesEFL/ESL Teaching and Learning

Cited by 102

Why Reinvent the Wheel: Let's Build Question Answering Systems Together

Singh, K., Lange, C., Vidal, M. E., Lehmann, J., Auer, S., Radhakrishna, A. S., Both, A., Shekarpour, S., Lytra, I., Usbeck, R., et al. (2018) · Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18

Topic ModelingNatural Language Processing Techniques

Cited by 102