Check computer science papers: citations, claims and retractions

Probing Neural Network Comprehension of Natural Language Arguments

Niven, T., & Kao, H.-Y. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 395

Make-A-Video: Text-to-Video Generation without Text-Video Data

Singer, U., Polyak, A., Hayes, T., Yin, X., An, J., Zhang, S., Hu, Q., Yang, H., Ashual, O., Gafni, O., et al. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 395

Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval

Liu, X., Gao, J., He, X., Deng, L., Duh, K., & Wang, Y.-Y. (2015) · Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingInformation Retrieval and Search Behavior

Cited by 395

K-Means Hashing: An Affinity-Preserving Quantization Method for Learning Binary Compact Codes

He, K., Wen, F., & Sun, J. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Image and Video Retrieval TechniquesImage Retrieval and Classification Techniques

Cited by 395

Toward an Ethics of Algorithms: Convening, Observation, Probability, and Timeliness

Ananny, M. (2016) · Science, Technology, & Human Values

Ethics and Social Impacts of AICybernetics and Technology in Society

Cited by 395

Can Large Language Models Provide Feedback to Students? A Case Study on ChatGPT

Dai, W., Lin, J., Jin, F., Li, T., Tsai, Y.-S., Gasevic, D., & Chen, G. (2023) · IEEE International Conference on Advanced Learning Technologies (ICALT)

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 395

Fusing local patterns of Gabor magnitude and phase for face recognition

Xie, S., Shan, S., Chen, X., & Chen, J. (2010) · IEEE Transactions on Image Processing

Face and Expression RecognitionFace recognition and analysis

Cited by 395

Can Large Language Models Provide Feedback to Students? A Case Study on ChatGPT

Dai, W., Lin, J., Jin, H., Li, T., Tsai, Y.-S., Gašević, D., & Chen, G. (2023) · 2023 IEEE International Conference on Advanced Learning Technologies (ICALT)

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 395

Quantum codes on a lattice with boundary

Bravyi, S. B., & Kitaev, A. Y. (1998) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 394

MultiPL-E: A Scalable and Polyglot Approach to Benchmarking Neural Code Generation

Cassano, F., Gouwar, J., Nguyen, D., Nguyen, S., Phipps-Costin, L., Pinckney, D., Yee, M.-H., Zi, Y., Anderson, C. J., Feldman, M. Q., et al. (2023) · IEEE Transactions on Software Engineering

Software Engineering ResearchTopic Modeling

Cited by 394

Fast High‐Dimensional Filtering Using the Permutohedral Lattice

Adams, A., Baek, J., & Davis, M. A. (2010) · Computer Graphics Forum

Computer Graphics and Visualization TechniquesImage and Signal Denoising Methods

Cited by 394

Federated learning enables big data for rare cancer boundary detection

Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications

Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification

Cited by 394

Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks

Golatkar, A., Achille, A., & Soatto, S. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 394

Where are human subjects in big data research? the emerging ethics divide

Metcalf, J., & Crawford, K. (2016) · Big Data & Society

Ethics and Social Impacts of AIBig Data Technologies and Applications

Cited by 394

Ensuring the data-rich future of the social sciences

King, G. (2011) · Science

Research Data Management PracticesData Analysis and Archiving

Cited by 394

STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing

Liu, M., Ding, Y., Xia, M., Liu, X., Ding, E., Zuo, W., & Wen, S. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 394

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Dua, D., Wang, Y., Dasigi, P., Stanovsky, G., Singh, S., & Gardner, M. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 393

Analog-to-Information Conversion via Random Demodulation

Kirolos, S., Laska, J., Wakin, M., Duarte, M., Baron, D., Ragheb, T., Massoud, Y., & Baraniuk, R. (2006) · 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software

Sparse and Compressive Sensing TechniquesMathematical Analysis and Transform Methods

Cited by 393

Test-Time Training with Self-Supervision for Generalization under Distribution Shifts

Sun, Y., Wang, X., Liu, Z., Miller, J., Efros, A. A., & Hardt, M. (2019) · arXiv

Domain Adaptation and Few-Shot LearningData Stream Mining Techniques

Cited by 393

Evaluating XAI: A comparison of rule-based and example-based explanations

van der Waa, J., Nieuwburg, E., Cremers, A., & Neerincx, M. (2021) · Artificial Intelligence

Explainable Artificial Intelligence (XAI)Usability and User Interface Design

Cited by 393

Cloud Quantum Computing of an Atomic Nucleus

Dumitrescu, E. F., McCaskey, A. J., Hagen, G., Jansen, G. R., Morris, T. D., Papenbrock, T., Pooser, R. C., Dean, D. J., & Lougovski, P. (2018) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureNuclear physics research studies

Cited by 393

Federated Learning for Vehicular Internet of Things: Recent Advances and Open Issues

Du, Z., Wu, C., Yoshinaga, T., Yau, K.-L. A., Ji, Y., & Li, J. (2020) · IEEE Open Journal of the Computer Society

Privacy-Preserving Technologies in DataVehicular Ad Hoc Networks (VANETs)

Cited by 393

Designing and Interpreting Probes with Control Tasks

Hewitt, J., & Liang, P. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Natural Language Processing TechniquesTopic Modeling

Cited by 393

Exponential suppression of bit or phase errors with cyclic error correction

Google Quantum, A. I., Chen, Z., Satzinger, K. J., Atalaya, J., Korotkov, A. N., Dunsworth, A., Sank, D., Quintana, C., McEwen, M., Barends, R., et al. (2021) · Nature

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 393