Check computer science papers: citations, claims and retractions

Trustworthy AI: From Principles to Practices

Li, B., Qi, P., Liu, B., Di, S., Liu, J., Pei, J., Yi, J., & Zhou, B. (2023) · ACM Computing Surveys

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 612

Distributional Reinforcement Learning With Quantile Regression

Dabney, W., Rowland, M., Bellemare, M., & Munos, R. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 612

Deconstructing Community-Based Collaborative Design: Towards More Equitable Participatory Design Engagements

Harrington, C., Erete, S., & Piper, A. M. (2019) · Proceedings of the ACM on Human-Computer Interaction

Innovative Human-Technology InteractionInnovative Approaches in Technology and Social Development

Cited by 612

Entity, Relation, and Event Extraction with Contextualized Span Representations

Wadden, D., Wennberg, U., Luan, Y., & Hajishirzi, H. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 612

The Success of Open Source

Weber, S. (2004) · Harvard University Press eBooks

Open Source Software InnovationsDigital Platforms and Economics

Cited by 611

To Predict and Serve?

Lum, K., & Isaac, W. (2016) · Significance

Ethics and Social Impacts of AIArtificial Intelligence in Law

Cited by 611

A NOVEL FAST IMAGE ENCRYPTION SCHEME BASED ON 3D CHAOTIC BAKER MAPS

MAO, Y., CHEN, G., & LIAN, S. (2004) · International Journal of Bifurcation and Chaos

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 611

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Gal, R., Alaluf, Y., Atzmon, Y., Patashnik, O., Bermano, A. H., Chechik, G., & Cohen-Or, D. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 611

End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks

Cheng, R., Orosz, G., Murray, R. M., & Burdick, J. W. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 611

Incorporating Convolution Designs into Visual Transformers

Yuan, K., Guo, S., Liu, Z., Zhou, A., Yu, F., & Wu, W. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 611

BM3D Frames and Variational Image Deblurring

Danielyan, A., Katkovnik, V., & Egiazarian, K. (2012) · IEEE Transactions on Image Processing

Image and Signal Denoising MethodsAdvanced Image Processing Techniques

Cited by 611

Prototypical Contrastive Learning of Unsupervised Representations

Li, J., Zhou, P., Xiong, C., & Hoi, S. C. H. (2020) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 611

Semantic Segmentation using Adversarial Networks

Luc, P., Couprie, C., Chintala, S., & Verbeek, J. (2016) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 611

DeepRoad: GAN-based metamorphic testing and input validation framework for autonomous driving systems

Zhang, M., Zhang, Y., Zhang, L., Liu, C., & Khurshid, S. (2018) · Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering

Software Testing and Debugging TechniquesAdversarial Robustness in Machine Learning

Cited by 611

The benefits and challenges of chatgpt: An overview

Deng, J., & Lin, Y. (2023) · Frontiers in Computing and Intelligent Systems

Speech and dialogue systemsTopic Modeling

Cited by 611

AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings

Kuziemski, M., & Misuraca, G. (2020) · Telecommunications Policy

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 610

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

Lu, Y., Bartolo, M., Moore, A., Riedel, S., & Stenetorp, P. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 610

DeepChain: Auditable and Privacy-Preserving Deep Learning with Blockchain-based Incentive

Weng, J., Weng, J., Zhang, J., Li, M., Zhang, Y., & Luo, W. (2019) · IEEE Transactions on Dependable and Secure Computing

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 610

Affective News: The Automated Coding of Sentiment in Political Texts

Young, L., & Soroka, S. (2012) · Political Communication

Sentiment Analysis and Opinion MiningComputational and Text Analysis Methods

Cited by 609

Help Seeking and Help Design in Interactive Learning Environments

Aleven, V., Stahl, E., Schworm, S., Fischer, F., & Wallace, R. (2003) · Review of Educational Research

Intelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning Methods

Cited by 609

Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation

Zhang, T., McCarthy, Z., Jow, O., Lee, D., Chen, X., Goldberg, K., & Abbeel, P. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 609

Generalizing Face Forgery Detection with High-frequency Features

Luo, Y., Zhang, Y., Yan, J., & Liu, W. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 609

Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation

Sheller, M. J., Reina, G. A., Edwards, B., Martin, J., & Bakas, S. (2019) · Lecture Notes in Computer Science

Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification

Cited by 609

Machine learning in acoustics: Theory and applications

Bianco, M. J., Gerstoft, P., Traer, J., Ozanich, E., Roch, M. A., Gannot, S., & Deledalle, C.-A. (2019) · The Journal of the Acoustical Society of America

Music and Audio ProcessingSpeech and Audio Processing

Cited by 609