Check computer science papers: citations, claims and retractions

Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation

Inoue, N., Furuta, R., Yamasaki, T., & Aizawa, K. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 616

AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents

Debenedetti, E., Zhang, J., Balunović, M., Beurer-Kellner, L., Fischer, M., & Tramèr, F. (2024) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 616

The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching

Heffernan, N. T., & Heffernan, C. L. (2014) · International Journal of Artificial Intelligence in Education

Intelligent Tutoring Systems and Adaptive LearningOnline Learning and Analytics

Cited by 616

Automatic photo pop-up

Hoiem, D., Efros, A. A., & Hebert, M. (2005) · ACM Transactions on Graphics

3D Shape Modeling and AnalysisComputer Graphics and Visualization Techniques

Cited by 616

Artificial intelligence for cybersecurity: Literature review and future research directions

Kaur, R., Gabrijelčič, D., & Klobučar, T. (2023) · Information Fusion

Network Security and Intrusion DetectionInformation and Cyber Security

Cited by 615

How Much Information?: Effects of Transparency on Trust in an Algorithmic Interface

Kizilcec, R. F. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 615

Probabilistic brains: knowns and unknowns

Pouget, A., Beck, J. M., Ma, W. J., & Latham, P. E. (2013) · Nature Neuroscience

Bayesian Modeling and Causal InferenceNeural dynamics and brain function

Cited by 615

The eNTERFACE’05 Audio-Visual Emotion Database

Martin, O., Kotsia, I., Macq, B., & Pitas, I. (2006) · 22nd International Conference on Data Engineering Workshops (ICDEW'06)

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 615

Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning

Shejwalkar, V., & Houmansadr, A. (2021) · Proceedings 2021 Network and Distributed System Security Symposium

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 615

A universal noise removal algorithm with an impulse detector

Garnett, R., Huegerich, T., Chui, C., & He, W. (2005) · IEEE Transactions on Image Processing

Image and Signal Denoising MethodsImage Enhancement Techniques

Cited by 615

Passage Re-ranking with BERT

Nogueira, R., & Cho, K. (2019) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 615

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

Lu, Y., Bartolo, M., Moore, A., Riedel, S., & Stenetorp, P. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 615

Towards a Human-like Open-Domain Chatbot

Adiwardana, D., Luong, M.-T., So, D. R., Hall, J., Fiedel, N., Thoppilan, R., Yang, Z., Kulshreshtha, A., Nemade, G., Lu, Y., et al. (2020) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 614

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

Wu, B., Wan, A., Iandola, F., Jin, P. H., & Keutzer, K. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 614

ProgPrompt: Generating Situated Robot Task Plans using Large Language Models

Singh, I., Blukis, V., Mousavian, A., Goyal, A., Xu, D., Tremblay, J., Fox, D., Thomason, J., & Garg, A. (2023) · 2023 IEEE International Conference on Robotics and Automation (ICRA)

AI-based Problem Solving and PlanningRobot Manipulation and Learning

Cited by 613

Diffusion policy: Visuomotor policy learning via action diffusion

Chi, C., Xu, Z., Feng, S., Cousineau, E., Du, Y., Burchfiel, B., Tedrake, R., & Song, S. (2025) · The International Journal of Robotics Research

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 613

Challenges, Methodologies, and Issues in the Usability Testing of Mobile Applications

Zhang, D., & Adipat, B. (2005) · International Journal of Human-Computer Interaction

Usability and User Interface DesignMobile and Web Applications

Cited by 613

Effective face frontalization in unconstrained images

Hassner, T., Harel, S., Paz, E., & Enbar, R. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Face recognition and analysisFace and Expression Recognition

Cited by 613

Comparison between geometry-based and Gabor-wavelets-based facial expression recognition using multi-layer perceptron

Zhang, Z., Lyons, M., Schuster, M., & Akamatsu, S. (2002) · Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition

Face and Expression RecognitionEmotion and Mood Recognition

Cited by 613

A Review of Domain Adaptation without Target Labels

Kouw, W. M., & Loog, M. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Domain Adaptation and Few-Shot LearningReinforcement Learning in Robotics

Cited by 613

Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices

Zhao, Y., Zhao, J., Jiang, L., Tan, R., Niyato, D., Li, Z., Lyu, L., & Liu, Y. (2021) · IEEE Internet of Things Journal

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 613

Universal Digital Quantum Simulation with Trapped Ions

Lanyon, B. P., Hempel, C., Nigg, D., Müller, M., Gerritsma, R., Zähringer, F., Schindler, P., Barreiro, J. T., Rambach, M., Kirchmair, G., et al. (2011) · Science

Quantum Computing Algorithms and ArchitectureCold Atom Physics and Bose-Einstein Condensates

Cited by 613

Multitask Prompted Training Enables Zero-Shot Task Generalization

Sanh, V., Webson, A., Raffel, C., Bach, S. H., Sutawika, L., Alyafeai, Z., Chaffin, A., Stiegler, A., Scao, T. L., Raja, A., et al. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 612

Identifying Mislabeled Training Data

Brodley, C. E., & Friedl, M. A. (1999) · Journal of Artificial Intelligence Research

Machine Learning and Data ClassificationMachine Learning and Algorithms

Cited by 612