Check computer science papers: citations, claims and retractions

Matryoshka Representation Learning

Kusupati, A., Bhatt, G., Rege, A., Wallingford, M., Sinha, A., Ramanujan, V., Howard-Snyder, W., Chen, K., Kakade, S., Jain, P., et al. (2022) · Advances in Neural Information Processing Systems 35

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 90

Developing an AI-based learning system for L2 learners’ authentic and ubiquitous learning in English language

Jia, F., Sun, D., Ma, Q., & Looi, C.-K. (2022) · Sustainability

Mobile Learning in EducationEnglish Language Learning and Teaching

Cited by 90

Improving Passage Retrieval with Zero-Shot Question Generation

Sachan, D., Lewis, M., Joshi, M., Aghajanyan, A., Yih, W.-T., Pineau, J., & Zettlemoyer, L. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Information Retrieval and Search BehaviorTopic Modeling

Cited by 90

Sketching NLP: A Case Study of Exploring the Right Things To Design with Language Intelligence

Yang, Q., Cranshaw, J., Amershi, S., Iqbal, S. T., & Teevan, J. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 90

Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets

Solaiman, I., & Dennison, C. (2021) · arXiv

Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection

Cited by 90

Mind the Gap: Assessing Temporal Generalization in Neural Language Models

Lazaridou, A., Kuncoro, A., Gribovskaya, E., Agrawal, D., Liska, A., Terzi, T., Gimenez, M., d'Autume, C. D. M., Kocisky, T., Ruder, S., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 90

Simulation of quantum random walks using the interference of a classical field

Jeong, H., Paternostro, M., & Kim, M. S. (2004) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications

Cited by 90

Integration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing: A summary of current methods

Chen, J., Zhao, M., Wang, X., Richard, C., & Rahardja, S. (2023) · IEEE Signal Processing Magazine

Remote-Sensing Image ClassificationAdvanced Image Fusion Techniques

Cited by 90

On the role of features in human activity recognition

Haresamudram, H., Anderson, D. V., & Plötz, T. (2019) · Proceedings of the 23rd International Symposium on Wearable Computers

Context-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Cited by 90

Structured Pruning of Neural Networks With Budget-Aware Regularization

Lemaire, C., Achkar, A., & Jodoin, P.-M. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 90

Universal discriminative quantum neural networks

Chen, H., Wossnig, L., Severini, S., Neven, H., & Mohseni, M. (2021) · Quantum Machine Intelligence

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 89

A Survey on Blockchain-based Identity Management and Decentralized Privacy for Personal Data

Gilani, K., Bertin, E., Hatin, J., & Crespi, N. (2020) · 2020 2nd Conference on Blockchain Research & Applications for Innovative Networks and Services (BRAINS)

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 89

Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning

Razeghi, Y., Logan IV, R. L., Gardner, M., & Singh, S. (2022) · Findings of the Association for Computational Linguistics: EMNLP 2022

Topic ModelingNatural Language Processing Techniques

Cited by 89

Perinasal Imaging of Physiological Stress and Its Affective Potential

Shastri, D., Papadakis, M., Tsiamyrtzis, P., Bass, B., & Pavlidis, I. (2012) · IEEE Transactions on Affective Computing

Emotion and Mood RecognitionInfrared Thermography in Medicine

Cited by 89

Machine learning and genomics: precision medicine versus patient privacy

Azencott, C.-A. (2018) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Privacy-Preserving Technologies in DataEthics in Clinical Research

Cited by 89

Multi-robot SLAM using condensed measurements

Lazaro, M. T., Paz, L. M., Pinies, P., Castellanos, J. A., & Grisetti, G. (2013) · 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

Robotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor Networks

Cited by 89

HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units

Hong, S., Xu, Y., Khare, A., Priambada, S., Maher, K., Aljiffry, A., Sun, J., & Tumanov, A. (2020) · Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 89

Scalable Fabric: flexible task management

Robertson, G., Horvitz, E., Czerwinski, M., Baudisch, P., Hutchings, D. R., Meyers, B., Robbins, D., & Smith, G. (2004) · Proceedings of the working conference on Advanced visual interfaces

Interactive and Immersive DisplaysPersonal Information Management and User Behavior

Cited by 89

Utilizing a wristband sensor to measure the stress level for people with dementia

Kikhia, B., Stavropoulos, T., Andreadis, S., Karvonen, N., Kompatsiaris, I., Sävenstedt, S., Pijl, M., & Melander, C. (2016) · Sensors

Context-Aware Activity Recognition SystemsEmotion and Mood Recognition

Cited by 89

Universal discriminative quantum neural networks

Chen, H., Wossnig, L., Severini, S., Neven, H., & Mohseni, M. (2018) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 89

Deploying multimodal learning analytics models to explore the impact of digital distraction and peer learning on student performance

Liao, C.-H., & Wu, J.-Y. (2022) · Computers & Education

Online Learning and AnalyticsEducational Technology in Learning

Cited by 89

Reliable emotion recognition system based on dynamic adaptive fusion of forehead biopotentials and physiological signals

Khezri, M., Firoozabadi, M., & Sharafat, A. R. (2015) · Computer Methods and Programs in Biomedicine

Emotion and Mood RecognitionHeart Rate Variability and Autonomic Control

Cited by 89

On the Use of Soft Computing Methods in Educational Data Mining and Learning Analytics Research: a Review of Years 2010–2018

Charitopoulos, A., Rangoussi, M., & Koulouriotis, D. (2020) · International Journal of Artificial Intelligence in Education

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 89

The loopholes of algorithmic public services: an “intelligent” accountability research agenda

Bracci, E. (2023) · Accounting, Auditing & Accountability Journal

Ethics and Social Impacts of AIE-Government and Public Services

Cited by 89