Check computer science papers: citations, claims and retractions

Counterventions: a reparative reflection on interventionist HCI

Williams, R. M., Boyd, L., & Gilbert, J. E. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionAssistive Technology in Communication and Mobility

Cited by 74

Community enhanced tutorials: improving tutorials with multiple demonstrations

Lafreniere, B., Grossman, T., & Fitzmaurice, G. (2013) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignIntelligent Tutoring Systems and Adaptive Learning

Cited by 74

Extraordinary computing: religion as a lens for reconsidering the home

Wyche, S. P., & Grinter, R. E. (2009) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionMedia, Religion, Digital Communication

Cited by 74

Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

Wang, Z., Mao, S., Wu, W., Ge, T., Wei, F., & Ji, H. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 74

Grammar-Constrained Decoding for Structured NLP Tasks without Finetuning

Geng, S., Josifoski, M., Peyrard, M., & West, R. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 74

Quantum gate learning in qubit networks: Toffoli gate without time-dependent control

Banchi, L., Pancotti, N., & Bose, S. (2016) · npj Quantum Information

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 74

Blockchain-Based VEC Network Trust Management: A DRL Algorithm for Vehicular Service Offloading and Migration

Ren, Y., Chen, X., Guo, S., Guo, S., & Xiong, A. (2021) · IEEE Transactions on Vehicular Technology

IoT and Edge/Fog ComputingVehicular Ad Hoc Networks (VANETs)

Cited by 74

Weather and surface condition detection based on road-side webcams: Application of pre-trained Convolutional Neural Network

Khan, M. N., & Ahmed, M. M. (2022) · International Journal of Transportation Science and Technology

Advanced Neural Network ApplicationsInfrastructure Maintenance and Monitoring

Cited by 74

Some Considerations on Learning to Explore via Meta-Reinforcement Learning

Stadie, B. C., Yang, G., Houthooft, R., Chen, X., Duan, Y., Wu, Y., Abbeel, P., & Sutskever, I. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 74

Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Embedded Inference

McKinstry, J. L., Esser, S. K., Appuswamy, R., Bablani, D., Arthur, J. V., Yildiz, I. B., & Modha, D. S. (2018) · arXiv

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 74

Contextual Outlier Interpretation

Liu, N., Shin, D., & Hu, X. (2018) · Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence

Anomaly Detection Techniques and ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 74

Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization

Miller, J., Taori, R., Raghunathan, A., Sagawa, S., Koh, P. W., Shankar, V., Liang, P., Carmon, Y., & Schmidt, L. (2021) · arXiv

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 74

Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora

Warstadt, A., Mueller, A., Choshen, L., Wilcox, E., Zhuang, C., Ciro, J., Mosquera, R., Paranjabe, B., Williams, A., Linzen, T., et al. (2023) · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning

Topic ModelingNatural Language Processing Techniques

Cited by 74

A Hybrid Workflow of Residual Convolutional Transformer Encoder for Breast Cancer Classification Using Digital X-ray Mammograms

Al-Tam, R. M., Al-Hejri, A. M., Narangale, S. M., Samee, N. A., Mahmoud, N. F., Al-masni, M. A., & Al-antari, M. A. (2022) · Biomedicines

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 74

Effects of Stereoscopic Viewing on Presence, Anxiety, and Cybersickness in a Virtual Reality Environment for Public Speaking

Ling, Y., Brinkman, W.-P., Nefs, H. T., Qu, C., & Heynderickx, I. (2012) · Presence: Teleoperators and Virtual Environments

Virtual Reality Applications and ImpactsAdvanced Optical Imaging Technologies

Cited by 74

Blockchain Technology in Financial Accounting: Enhancing Transparency, Security, and ESG Reporting

Almadadha, R. (2024) · Blockchains

Blockchain Technology Applications and SecurityAccounting and Financial Management

Cited by 74

Dual Graph Convolutional Networks with Transformer and Curriculum Learning for Image Captioning

Dong, X., Long, C., Xu, W., & Xiao, C. (2021) · Proceedings of the 29th ACM International Conference on Multimedia

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 74

Development of an automated speech recognition interface for personal emergency response systems

Hamill, M., Young, V., Boger, J., & Mihailidis, A. (2009) · Journal of NeuroEngineering and Rehabilitation

Speech and dialogue systemsTechnology Use by Older Adults

Cited by 74

Toward Objective Monitoring of Ingestive Behavior in Free‐living Population

Sazonov, E. S., Schuckers, S. A. C., Lopez‐Meyer, P., Makeyev, O., Melanson, E. L., Neuman, M. R., & Hill, J. O. (2009) · Obesity

Context-Aware Activity Recognition SystemsNutrition, Health and Food Behavior

Cited by 74

SnapKV: LLM Knows What You are Looking for Before Generation

Li, Y., Huang, Y., Yang, B., Venkitesh, B., Locatelli, A., Ye, H., Cai, T., Lewis, P., & Chen, D. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 74

Mastering Deepfake Detection: A Cutting-Edge Approach to Distinguish GAN and Diffusion-Model Images

Guarnera, L., Giudice, O., & Battiato, S. (2024) · ACM Transactions on Multimedia Computing, Communications, and Applications

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 74

Assessment of natural language processing of electronic health records to measure goals-of-care discussions as a clinical trial outcome

Lee, R. Y., Kross, E. K., Torrence, J., Li, K. S., Sibley, J., Cohen, T., Lober, W. B., Engelberg, R. A., & Curtis, J. R. (2023) · JAMA Network Open

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 74

HybridFlow: A Flexible and Efficient RLHF Framework

Sheng, G., Zhang, C., Ye, Z., Wu, X., Zhang, W., Zhang, R., Peng, Y., Lin, H., & Wu, C. (2025) · Proceedings of the Twentieth European Conference on Computer Systems

Parallel Computing and Optimization TechniquesScientific Computing and Data Management

Cited by 74

What Virtual Reality Research in Addictions Can Tell Us about the Future of Obesity Assessment and Treatment

Bordnick, P. S., Carter, B. L., & Traylor, A. C. (2011) · Journal of Diabetes Science and Technology

Virtual Reality Applications and ImpactsEating Disorders and Behaviors

Cited by 74