Check computer science papers: citations, claims and retractions

3D Graph Neural Networks for RGBD Semantic Segmentation

Qi, X., Liao, R., Jia, J., Fidler, S., & Urtasun, R. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

3D Shape Modeling and AnalysisAdvanced Neural Network Applications

Cited by 482

Rico: A Mobile App Dataset for Building Data-Driven Design Applications

Deka, B., Huang, Z., Franzen, C., Hibschman, J., Afergan, D., Li, Y., Nichols, J., & Kumar, R. (2017) · Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology

Usability and User Interface DesignMobile and Web Applications

Cited by 482

A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges

McEnroe, P., Wang, S., & Liyanage, M. (2022) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingUAV Applications and Optimization

Cited by 482

CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotation of Modality

Yu, W., Xu, H., Meng, F., Zhu, Y., Ma, Y., Wu, J., Zou, J., & Yang, K. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 482

Recommender Systems in the Era of Large Language Models (LLMs)

Zhao, Z., Fan, W., Li, J., Liu, Y., Mei, X., Wang, Y., Wen, Z., Wang, F., Zhao, X., Tang, J., et al. (2024) · IEEE Transactions on Knowledge and Data Engineering

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 481

Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge

Campello, V. M., Gkontra, P., Izquierdo, C., Martin-Isla, C., Sojoudi, A., Full, P. M., Maier-Hein, K., Zhang, Y., He, Z., Ma, J., et al. (2021) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesCardiac Imaging and Diagnostics

Cited by 481

Fast and Robust Neural Network Joint Models for Statistical Machine Translation

Devlin, J., Zbib, R., Huang, Z., Lamar, T., Schwartz, R., & Makhoul, J. (2014) · Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesSpeech Recognition and Synthesis

Cited by 481

Progressive Feature Alignment for Unsupervised Domain Adaptation

Chen, C., Xie, W., Huang, W., Rong, Y., Ding, X., Huang, Y., Xu, T., & Huang, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 481

Quasi-Dense Similarity Learning for Multiple Object Tracking

Pang, J., Qiu, L., Li, X., Chen, H., Li, Q., Darrell, T., & Yu, F. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 480

Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results

Li, X., Gu, Y., Dvornek, N., Staib, L. H., Ventola, P., & Duncan, J. S. (2020) · Medical Image Analysis

Privacy-Preserving Technologies in DataFunctional Brain Connectivity Studies

Cited by 480

Residual Reinforcement Learning for Robot Control

Johannink, T., Bahl, S., Nair, A., Luo, J., Kumar, A., Loskyll, M., Ojea, J. A., Solowjow, E., & Levine, S. (2019) · 2019 International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 480

Handwritten digit recognition: applications of neural network chips and automatic learning

Le Cun, Y., Jackel, L. D., Boser, B., Denker, J. S., Graf, H. P., Guyon, I., Henderson, D., Howard, R. E., & Hubbard, W. (1989) · IEEE Communications Magazine

Handwritten Text Recognition TechniquesNeural Networks and Applications

Cited by 480

Diversity is All You Need: Learning Skills without a Reward Function

Eysenbach, B., Gupta, A., Ibarz, J., & Levine, S. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 480

On Variational Bounds of Mutual Information

Poole, B., Ozair, S., Oord, A. V. D., Alemi, A. A., & Tucker, G. (2019) · arXiv

Stochastic Gradient Optimization TechniquesGaussian Processes and Bayesian Inference

Cited by 480

Quantum Generative Adversarial Networks for learning and loading random distributions

Zoufal, C., Lucchi, A., & Woerner, S. (2019) · npj Quantum Information

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 480

Holistic Evaluation of Language Models

Bommasani, R., Liang, P., & Lee, T. (2023) · Annals of the New York Academy of Sciences

Topic ModelingNatural Language Processing Techniques

Cited by 480

Animated agents for procedural training in virtual reality: Perception, cognition, and motor control

Rickel, J., & Johnson, W. L. (1999) · Applied Artificial Intelligence

Intelligent Tutoring Systems and Adaptive LearningSocial Robot Interaction and HRI

Cited by 480

The power of gifts: organizing social relationships in open source communities

Bergquist, M., & Ljungberg, J. (2001) · Information Systems Journal

Open Source Software InnovationsKnowledge Management and Sharing

Cited by 480

HoloClean: holistic data repairs with probabilistic inference

Rekatsinas, T., Chu, X., Ilyas, I. F., & Ré, C. (2017) · Proceedings of the VLDB Endowment

Data Quality and ManagementAdvanced Database Systems and Queries

Cited by 480

GraphCodeBERT: Pre-training Code Representations with Data Flow

Guo, D., Ren, S., Lu, S., Feng, Z., Tang, D., Liu, S., Zhou, L., Duan, N., Svyatkovskiy, A., Fu, S., et al. (2020) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 480

Deep multimodal data fusion

Zhao, F., Zhang, C., & Geng, B. (2024) · ACM Computing Surveys

Multimodal Machine Learning ApplicationsAdvanced Image Fusion Techniques

Cited by 480

Survey on Chatbot Design Techniques in Speech Conversation Systems

A., S., & John, D. (2015) · International Journal of Advanced Computer Science and Applications

Speech and dialogue systemsAI in Service Interactions

Cited by 479

A Survey of Lightweight-Cryptography Implementations

Eisenbarth, T., Kumar, S., Paar, C., Poschmann, A., & Uhsadel, L. (2007) · IEEE Design & Test of Computers

Cryptographic Implementations and SecurityCryptography and Residue Arithmetic

Cited by 479

Certified Defenses for Data Poisoning Attacks

Steinhardt, J., Koh, P. W., & Liang, P. (2017) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 479