Check computer science papers: citations, claims and retractions

CLIP-Q: Deep Network Compression Learning by In-parallel Pruning-Quantization

Tung, F., & Mori, G. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 220

Magic State Distillation: Not as Costly as You Think

Litinski, D. (2019) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 220

Selective Classification for Deep Neural Networks

Geifman, Y., & El-Yaniv, R. (2017) · arXiv

Advanced Neural Network ApplicationsAdversarial Robustness in Machine Learning

Cited by 220

Semantics-based obfuscation-resilient binary code similarity comparison with applications to software plagiarism detection

Luo, L., Ming, J., Wu, D., Liu, P., & Zhu, S. (2014) · Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering

Software Engineering ResearchAcademic integrity and plagiarism

Cited by 220

GeDi: Generative Discriminator Guided Sequence Generation

Krause, B., Gotmare, A. D., McCann, B., Keskar, N. S., Joty, S., Socher, R., & Rajani, N. F. (2021) · Findings of the Association for Computational Linguistics: EMNLP 2021

Topic ModelingNatural Language Processing Techniques

Cited by 220

NeMo Guardrails: A Toolkit for Controllable and Safe LLM Applications with Programmable Rails

Rebedea, T., Dinu, R., Sreedhar, M. N., Parisien, C., & Cohen, J. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 220

On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines

Mosbach, M., Andriushchenko, M., & Klakow, D. (2020) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 220

Localization Distillation for Dense Object Detection

Zheng, Z., Ye, R., Wang, P., Ren, D., Zuo, W., Hou, Q., & Cheng, M.-M. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 220

A survey on few-shot class-incremental learning

Tian, S., Li, L., Li, W., Ran, H., Ning, X., & Tiwari, P. (2024) · Neural Networks

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 220

Measuring and improving consistency in pretrained language models

Elazar, Y., Kassner, N., Ravfogel, S., Ravichander, A., Hovy, E., Schütze, H., & Goldberg, Y. (2021) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 220

Trust calibration within a human-robot team: Comparing automatically generated explanations

Wang, N., Pynadath, D. V., & Hill, S. G. (2016) · 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

Explainable Artificial Intelligence (XAI)Social Robot Interaction and HRI

Cited by 220

On‐line prediction of fermentation variables using neural networks

Thibault, J., Van Breusegem, V., & Chéruy, A. (1990) · Biotechnology and Bioengineering

Neural Networks and ApplicationsControl Systems and Identification

Cited by 220

Sitemaps, storyboards, and specifications: a sketch of Web site design practice

Newman, M. W., & Landay, J. A. (2000) · Proceedings of the 3rd conference on Designing interactive systems: processes, practices, methods, and techniques

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 220

Backdoor Attacks to Graph Neural Networks

Zhang, Z., Jia, J., Wang, B., & Gong, N. Z. (2021) · Proceedings of the 26th ACM Symposium on Access Control Models and Technologies

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 220

DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

Qi, H., Guo, Q., Juefei-Xu, F., Xie, X., Ma, L., Feng, W., Liu, Y., & Zhao, J. (2020) · Proceedings of the 28th ACM International Conference on Multimedia

Digital Media Forensic DetectionFace recognition and analysis

Cited by 220

Deep Reinforcement Learning-Based Mode Selection and Resource Management for Green Fog Radio Access Networks

Sun, Y., Peng, M., & Mao, S. (2019) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingAdvanced Wireless Network Optimization

Cited by 219

Stochastic gradient descent for hybrid quantum-classical optimization

Sweke, R., Wilde, F., Meyer, J., Schuld, M., Faehrmann, P. K., Meynard-Piganeau, B., & Eisert, J. (2020) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 219

Exploring the Regularity of Sparse Structure in Convolutional Neural Networks

Mao, H., Han, S., Pool, J., Li, W., Liu, X., Wang, Y., & Dally, W. J. (2017) · arXiv

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 219

Class-level spectral features for emotion recognition

Bitouk, D., Verma, R., & Nenkova, A. (2010) · Speech Communication

Emotion and Mood RecognitionSpeech Recognition and Synthesis

Cited by 219

On Stopwords, Filtering and Data Sparsity for Sentiment Analysis of Twitter

Saif, H., Fernandez, M., He, Y., & Alani, H. (2014) · Proceedings of the Language Resources and Evaluation Conference

Sentiment Analysis and Opinion MiningText and Document Classification Technologies

Cited by 219

Diverse Beam Search for Improved Description of Complex Scenes

Vijayakumar, A., Cogswell, M., Selvaraju, R., Sun, Q., Lee, S., Crandall, D., & Batra, D. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Multimodal Machine Learning ApplicationsNatural Language Processing Techniques

Cited by 219

Investigating Explainability of Generative AI for Code through Scenario-based Design

Sun, J., Liao, Q. V., Muller, M., Agarwal, M., Houde, S., Talamadupula, K., & Weisz, J. D. (2022) · 27th International Conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)Software Engineering Research

Cited by 219

RSGPT: A Remote Sensing Vision Language Model and Benchmark

Hu, Y., Yuan, J., Wen, C., Lu, X., & Li, X. (2023) · arXiv

Multimodal Machine Learning ApplicationsRemote-Sensing Image Classification

Cited by 219

Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation

Zhang, Q., Zhang, J., Liu, W., & Tao, D. (2019) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 219