Check computer science papers: citations, claims and retractions

Scalable Webcam Eye Tracking by Learning from User Interactions

Papoutsaki, A. (2015) · Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems

Gaze Tracking and Assistive TechnologyVisual Attention and Saliency Detection

Cited by 92

COCOA: Cross Modality Contrastive Learning for Sensor Data

Deldari, S., Xue, H., Saeed, A., Smith, D. V., & Salim, F. D. (2022) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Domain Adaptation and Few-Shot LearningContext-Aware Activity Recognition Systems

Cited by 92

The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domain

Moskvichev, A., Odouard, V. V., & Mitchell, M. (2023) · arXiv

AI-based Problem Solving and PlanningDomain Adaptation and Few-Shot Learning

Cited by 92

Tight, robust, and feasible quantum speed limits for open dynamics

Campaioli, F., Pollock, F. A., & Modi, K. (2019) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 92

Large Language Models in Cybersecurity: State-of-the-Art

Motlagh, F. N., Hajizadeh, M., Majd, M., Najafi, P., Cheng, F., & Meinel, C. (2024) · arXiv

Adversarial Robustness in Machine LearningNetwork Security and Intrusion Detection

Cited by 92

What can AI do for me?: evaluating machine learning interpretations in cooperative play

Feng, S., & Boyd-Graber, J. (2019) · Proceedings of the 24th International Conference on Intelligent User Interfaces

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

Cited by 92

A Survey on Mixture of Experts

Cai, W., Jiang, J., Wang, F., Tang, J., Kim, S., & Huang, J. (2024)

Advanced Neural Network ApplicationsTopic Modeling

Cited by 92

The landscape of persuasive technologies

King, P., & Tester, J. (1999) · Communications of the ACM

Innovative Human-Technology InteractionPsychology of Social Influence

Cited by 92

Towards Knowledge-Based Personalized Product Description Generation in E-commerce

Chen, Q., Lin, J., Zhang, Y., Yang, H., Zhou, J., & Tang, J. (2019) · Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Topic ModelingInformation Retrieval and Search Behavior

Cited by 92

Language Models as Agent Models

Andreas, J. (2022) · Findings of the Association for Computational Linguistics: EMNLP 2022

Natural Language Processing TechniquesTopic Modeling

Cited by 92

Generalization and Regularization in DQN

Farebrother, J., Machado, M. C., & Bowling, M. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 92

The Ladder: A Reliable Leaderboard for Machine Learning Competitions

Blum, A., & Hardt, M. (2015) · arXiv

Machine Learning and Data ClassificationAdvanced Bandit Algorithms Research

Cited by 92

Large Language Models in Cybersecurity: State-of-the-Art

Motlagh, F., Hajizadeh, M., Majd, M., Najafi, P., Cheng, F., & Meinel, C. (2025) · Proceedings of the 11th International Conference on Information Systems Security and Privacy

Adversarial Robustness in Machine LearningNetwork Security and Intrusion Detection

Cited by 92

LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning

Chen, S., Chen, X., Zhang, C., Li, M., Yu, G., Fei, H., Zhu, H., Fan, J., & Chen, T. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning Applications3D Shape Modeling and Analysis

Cited by 92

CodeT: Code Generation with Generated Tests

Chen, B., Zhang, F., Nguyen, A., Zan, D., Lin, Z., Lou, J.-G., & Chen, W. (2022) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 92

How to Prompt? Opportunities and Challenges of Zero- and Few-Shot Learning for Human-AI Interaction in Creative Applications of Generative Models

Dang, H., Mecke, L., Lehmann, F., Goller, S., & Buschek, D. (2022) · arXiv

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 92

Automotive big data: Applications, workloads and infrastructures

Luckow, A., Kennedy, K., Manhardt, F., Djerekarov, E., Vorster, B., & Apon, A. (2015) · 2015 IEEE International Conference on Big Data (Big Data)

Cloud Computing and Resource ManagementBig Data Technologies and Applications

Cited by 92

Assessment of deforestation in the Lower Amazon floodplain using historical Landsat MSS/TM imagery

Renó, V. F., Novo, E. M. L. M., Suemitsu, C., Rennó, C. D., & Silva, T. S. F. (2011) · Remote Sensing of Environment

Remote-Sensing Image ClassificationRemote Sensing in Agriculture

Cited by 92

ProtoHAR: Prototype Guided Personalized Federated Learning for Human Activity Recognition

Cheng, D., Zhang, L., Bu, C., Wang, X., Wu, H., & Song, A. (2023) · IEEE Journal of Biomedical and Health Informatics

Privacy-Preserving Technologies in DataContext-Aware Activity Recognition Systems

Cited by 92

CodePlan: Repository-level Coding using LLMs and Planning

Bairi, R., Sonwane, A., Kanade, A., C, V. D., Iyer, A., Parthasarathy, S., Rajamani, S., Ashok, B., & Shet, S. (2023) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 92

A Simple and Effective Pruning Approach for Large Language Models

Sun, M., Liu, Z., Bair, A., & Kolter, J. Z. (2023) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 92

Record and Reward Federated Learning Contributions with Blockchain

Martinez, I., Francis, S., & Hafid, A. S. (2019) · 2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

Blockchain Technology Applications and SecurityPrivacy-Preserving Technologies in Data

Cited by 92

Data-Efficient Generalization of Robot Skills with Contextual Policy Search

Kupcsik, A., Deisenroth, M., Peters, J., & Neumann, G. (2013) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 92

Charformer: Fast Character Transformers via Gradient-based Subword Tokenization

Tay, Y., Tran, V. Q., Ruder, S., Gupta, J., Chung, H. W., Bahri, D., Qin, Z., Baumgartner, S., Yu, C., & Metzler, D. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 92