Check computer science papers: citations, claims and retractions

A Framework for Malicious Traffic Detection in IoT Healthcare Environment

Hussain, F., Abbas, S. G., Shah, G. A., Pires, I. M., Fayyaz, U. U., Shahzad, F., Garcia, N. M., & Zdravevski, E. (2021) · Sensors

Network Security and Intrusion DetectionInternet of Things and AI

Cited by 230

What is DevOps?: A Systematic Mapping Study on Definitions and Practices

Jabbari, R., bin Ali, N., Petersen, K., & Tanveer, B. (2016) · Proceedings of the Scientific Workshop Proceedings of XP2016

Software Engineering Techniques and PracticesSoftware System Performance and Reliability

Cited by 230

Large Language Models Can Self-Improve

Huang, J., Gu, S. S., Hou, L., Wu, Y., Wang, X., Yu, H., & Han, J. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 230

A Scalable Algorithm for Tracking an Unknown Number of Targets Using Multiple Sensors

Meyer, F., Braca, P., Willett, P., & Hlawatsch, F. (2017) · IEEE Transactions on Signal Processing

Target Tracking and Data Fusion in Sensor NetworksInertial Sensor and Navigation

Cited by 230

Prostate cancer detection using deep convolutional neural networks

Yoo, S., Gujrathi, I., Haider, M. A., & Khalvati, F. (2019) · Scientific Reports

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 230

Skeleton-aware networks for deep motion retargeting

Aberman, K., Li, P., Lischinski, D., Sorkine-Hornung, O., Cohen-Or, D., & Chen, B. (2020) · ACM Transactions on Graphics

Human Motion and Animation3D Shape Modeling and Analysis

Cited by 230

LongT5: Efficient Text-To-Text Transformer for Long Sequences

Guo, M., Ainslie, J., Uthus, D., Ontanon, S., Ni, J., Sung, Y.-H., & Yang, Y. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 230

A Systematic Review of Deep Learning Approaches to Educational Data Mining

Hernández-Blanco, A., Herrera-Flores, B., Tomás, D., & Navarro-Colorado, B. (2019) · Complexity

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 230

Deep Reinforcement Learning for Sequence-to-Sequence Models

Keneshloo, Y., Shi, T., Ramakrishnan, N., & Reddy, C. K. (2019) · IEEE Transactions on Neural Networks and Learning Systems

Topic ModelingNatural Language Processing Techniques

Cited by 230

LongT5: Efficient Text-To-Text Transformer for Long Sequences

Guo, M., Ainslie, J., Uthus, D., Ontanon, S., Ni, J., Sung, Y.-H., & Yang, Y. (2022) · Findings of the Association for Computational Linguistics: NAACL 2022

Topic ModelingNatural Language Processing Techniques

Cited by 230

MARTA GANs: unsupervised representation learning for remote sensing image classification

Lin, D., Fu, K., Wang, Y., Xu, G., & Sun, X. (2017) · IEEE Geoscience and Remote Sensing Letters

Remote-Sensing Image ClassificationAdvanced Neural Network Applications

Cited by 230

Emotion Recognition using Multimodal Residual LSTM Network

Ma, J., Tang, H., Zheng, W.-L., & Lu, B.-L. (2019) · Proceedings of the 27th ACM International Conference on Multimedia

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 230

Influence Diagrams for Causal Modelling and Inference

Dawid, A. P. (2002) · International Statistical Review

Bayesian Modeling and Causal InferenceLogic, Reasoning, and Knowledge

Cited by 230

Large Language Models Can Self-Improve

Huang, J., Gu, S., Hou, L., Wu, Y., Wang, X., Yu, H., & Han, J. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 230

Human-like systematic generalization through a meta-learning neural network

Lake, B. M., & Baroni, M. (2023) · Nature

Neural Networks and ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 230

The star user interface: an overview

Smith, D. C., Irby, C., Kimball, R., & Harslem, E. (1982) · Proceedings of the June 7-10, 1982, national computer conference on - AFIPS '82

Usability and User Interface DesignInteractive and Immersive Displays

Cited by 230

Multimodal Language Analysis with Recurrent Multistage Fusion

Liang, P. P., Liu, Z., Bagher Zadeh, A., & Morency, L.-P. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Multimodal Machine Learning ApplicationsSentiment Analysis and Opinion Mining

Cited by 230

Locating and Editing Factual Associations in GPT

Meng, K., Bau, D., Andonian, A., & Belinkov, Y. (2022) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 230

Persuasive system design: state of the art and future directions

Torning, K., & Oinas-Kukkonen, H. (2009) · Proceedings of the 4th International Conference on Persuasive Technology

Innovative Human-Technology InteractionMedia Influence and Health

Cited by 230

Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods

van Giffen, B., Herhausen, D., & Fahse, T. (2022) · Journal of Business Research

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 230

AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models

Zhu, S., Zhang, R., An, B., Wu, G., Barrow, J., Wang, Z., Huang, F., Nenkova, A., & Sun, T. (2023) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 230

Do Automatically Generated Unit Tests Find Real Faults? An Empirical Study of Effectiveness and Challenges (T)

Shamshiri, S., Just, R., Rojas, J. M., Fraser, G., McMinn, P., & Arcuri, A. (2015) · 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)

Software Testing and Debugging TechniquesSoftware Engineering Research

Cited by 230

Towards Automated Log Parsing for Large-Scale Log Data Analysis

He, P., Zhu, J., He, S., Li, J., & Lyu, M. R. (2018) · IEEE Transactions on Dependable and Secure Computing

Software System Performance and ReliabilityAdvanced Database Systems and Queries

Cited by 230

Multimodal emotion recognition using EEG and eye tracking data

Zheng, W.-L., Dong, B.-N., & Lu, B.-L. (2014) · 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 230