Check computer science papers: citations, claims and retractions

Future applications of generative large language models: a data-driven case study on ChatGPT

Chiarello, F., Giordano, V., Spada, I., Barandoni, S., & Fantoni, G. (2024) · Technovation

Topic ModelingArtificial Intelligence Applications

Cited by 164

Spatial Search by Quantum Walk is Optimal for Almost all Graphs

Chakraborty, S., Novo, L., Ambainis, A., & Omar, Y. (2016) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 164

An empirical characterization of fair machine learning for clinical risk prediction

Pfohl, S. R., Foryciarz, A., & Shah, N. H. (2021) · Journal of Biomedical Informatics

Ethics and Social Impacts of AIMachine Learning in Healthcare

Cited by 164

Eye, Head and Torso Coordination During Gaze Shifts in Virtual Reality

Sidenmark, L., & Gellersen, H. (2020) · ACM Transactions on Computer-Human Interaction

Gaze Tracking and Assistive TechnologyInteractive and Immersive Displays

Cited by 163

Aligning Knowledge and Text Embeddings by Entity Descriptions

Zhong, H., Zhang, J., Wang, Z., Wan, H., & Chen, Z. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

Topic ModelingAdvanced Graph Neural Networks

Cited by 163

Evaluating saliency map explanations for convolutional neural networks: a user study

Alqaraawi, A., Schuessler, M., Weiß, P., Costanza, E., & Berthouze, N. (2020) · Proceedings of the 25th International Conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)Visual Attention and Saliency Detection

Cited by 163

DeepMood: Forecasting Depressed Mood Based on Self-Reported Histories via Recurrent Neural Networks

Suhara, Y., Xu, Y., & Pentland, A. '. (2017) · Proceedings of the 26th International Conference on World Wide Web

Emotion and Mood RecognitionMental Health via Writing

Cited by 163

Consistent updates for software-defined networks: change you can believe in!

Reitblatt, M., Foster, N., Rexford, J., & Walker, D. (2011) · Proceedings of the 10th ACM Workshop on Hot Topics in Networks

Software-Defined Networks and 5GDistributed systems and fault tolerance

Cited by 163

Stacked capsule autoencoders

Kosiorek, A. R., Sabour, S., Teh, Y. W., & Hinton, G. E. (2019) · arXiv

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 163

The Sense of Confidence during Probabilistic Learning: A Normative Account

Meyniel, F., Schlunegger, D., & Dehaene, S. (2015) · PLOS Computational Biology

Bayesian Modeling and Causal InferenceMemory and Neural Mechanisms

Cited by 163

RTbust: Exploiting Temporal Patterns for Botnet Detection on Twitter

Mazza, M., Cresci, S., Avvenuti, M., Quattrociocchi, W., & Tesconi, M. (2019) · Proceedings of the 10th ACM Conference on Web Science

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 163

Resource-efficient digital quantum simulation of d-level systems for photonic, vibrational, and spin-s Hamiltonians

Sawaya, N. P. D., Menke, T., Kyaw, T. H., Johri, S., Aspuru-Guzik, A., & Guerreschi, G. G. (2020) · npj Quantum Information

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 163

Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning

Baik, S., Choi, J., Kim, H., Cho, D., Min, J., & Lee, K. M. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningMachine Learning and Data Classification

Cited by 163

FDML: A Collaborative Machine Learning Framework for Distributed Features

Hu, Y., Niu, D., Yang, J., & Zhou, S. (2019) · Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 163

SMS for Life: a pilot project to improve anti-malarial drug supply management in rural Tanzania using standard technology

Barrington, J., Wereko-Brobby, O., Ward, P., Mwafongo, W., & Kungulwe, S. (2010) · Malaria Journal

ICT in Developing CommunitiesMobile Health and mHealth Applications

Cited by 163

Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study

Cao, Y., Zhou, L., Lee, S., Cabello, L., Chen, M., & Hershcovich, D. (2023) · Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP)

Ethics and Social Impacts of AITopic Modeling

Cited by 163

Hybrid Deep Neural Network--Hidden Markov Model (DNN-HMM) Based Speech Emotion Recognition

Li, L., Zhao, Y., Jiang, D., Zhang, Y., Wang, F., Gonzalez, I., Valentin, E., & Sahli, H. (2013) · 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction

Speech Recognition and SynthesisEmotion and Mood Recognition

Cited by 163

On the application of blockchains to spectrum management

Weiss, M. B. H., Werbach, K., Sicker, D. C., & Bastidas, C. E. C. (2019) · IEEE Transactions on Cognitive Communications and Networking

Cognitive Radio Networks and Spectrum SensingBlockchain Technology Applications and Security

Cited by 163

Chisel: Real Time Large Scale 3D Reconstruction Onboard a Mobile Device using Spatially Hashed Signed Distance Fields

Klingensmith, M., Dryanovski, I., Srinivasa, S., & Xiao, J. (2015) · Robotics: Science and Systems XI

3D Shape Modeling and AnalysisRobotics and Sensor-Based Localization

Cited by 163

A benchmark dataset to evaluate sensor displacement in activity recognition

Baños, O., Damas, M., Pomares, H., Rojas, I., Tóth, M. A., & Amft, O. (2012) · Proceedings of the 2012 ACM Conference on Ubiquitous Computing

Context-Aware Activity Recognition SystemsPhysical Activity and Health

Cited by 163

Usability evaluation of mobile applications using ISO 9241 and ISO 25062 standards

Moumane, K., Idri, A., & Abran, A. (2016) · SpringerPlus

Usability and User Interface DesignMobile and Web Applications

Cited by 163

Analyzing the problem of unsustainable health information systems in less-developed economies: Case studies from Tanzania and Mozambique

Kimaro, H. C., & Nhampossa, J. L. (2005) · Information Technology for Development

ICT in Developing CommunitiesInformation Systems Theories and Implementation

Cited by 163

A Reinforcement Learning Framework for Explainable Recommendation

Wang, X., Chen, Y., Yang, J., Wu, L., Wu, Z., & Xie, X. (2018) · 2018 IEEE International Conference on Data Mining (ICDM)

Recommender Systems and TechniquesExplainable Artificial Intelligence (XAI)

Cited by 163

Using information fragments to answer the questions developers ask

Fritz, T., & Murphy, G. C. (2010) · Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 163