Check computer science papers: citations, claims and retractions

Efficient Attentions for Long Document Summarization

Huang, L., Cao, S., Parulian, N., Ji, H., & Wang, L. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingAdvanced Text Analysis Techniques

Cited by 146

User-adaptive information visualization: using eye gaze data to infer visualization tasks and user cognitive abilities

Steichen, B., Carenini, G., & Conati, C. (2013) · Proceedings of the 2013 international conference on Intelligent user interfaces

Data Visualization and AnalyticsGaze Tracking and Assistive Technology

Cited by 146

Robustness and Precision: How Data Quality May Influence Key Dependent Variables in Infant Eye‐Tracker Analyses

Wass, S. V., Forssman, L., & Leppänen, J. (2014) · Infancy

Gaze Tracking and Assistive TechnologyChild and Animal Learning Development

Cited by 146

Virtual reality exposure in anxiety disorders: Impact on psychophysiological reactivity

Diemer, J., Mühlberger, A., Pauli, P., & Zwanzger, P. (2014) · The World Journal of Biological Psychiatry

Virtual Reality Applications and ImpactsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Cited by 146

Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis

Marya, N. B., Powers, P. D., Chari, S. T., Gleeson, F. C., Leggett, C. L., Abu Dayyeh, B. K., Chandrasekhara, V., Iyer, P. G., Majumder, S., Pearson, R. K., et al. (2021) · Gut

AI in cancer detectionIgG4-Related and Inflammatory Diseases

Cited by 146

The AI Index 2022 Annual Report

Zhang, D., Maslej, N., Brynjolfsson, E., Etchemendy, J., Lyons, T., Manyika, J., Ngo, H., Niebles, J. C., Sellitto, M., Sakhaee, E., et al. (2022) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 146

Nearest Neighbour Searches and the Curse of Dimensionality

MARIMONT, R. B., & SHAPIRO, M. B. (1979) · IMA Journal of Applied Mathematics

Data Management and AlgorithmsAdvanced Clustering Algorithms Research

Cited by 146

An efficient instance selection algorithm to reconstruct training set for support vector machine

Liu, C., Wang, W., Wang, M., Lv, F., & Konan, M. (2017) · Knowledge-Based Systems

Machine Learning and Data ClassificationData Mining and Machine Learning Applications

Cited by 146

Multi-modal learning from unpaired images: application to multi-organ segmentation in CT and MRI

Valindria, V. V., Pawlowski, N., Rajchl, M., Lavdas, I., Aboagye, E. O., Rockall, A. G., Rueckert, D., & Glocker, B. (2018) · 2018 IEEE Winter Conference on Applications of Computer Vision (WACV)

Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning

Cited by 146

New product ideas from lead users

von Hippel, E. (1989) · Research-Technology Management

Open Source Software InnovationsService and Product Innovation

Cited by 146

Survey and analysis of hallucinations in large language models: attribution to prompting strategies or model behavior

Anh-Hoang, D., Tran, V., & Nguyen, L.-M. (2025) · Frontiers in Artificial Intelligence

Topic ModelingNatural Language Processing Techniques

Cited by 146

Masked reconstruction based self-supervision for human activity recognition

Haresamudram, H., Beedu, A., Agrawal, V., Grady, P. L., Essa, I., Hoffman, J., & Plötz, T. (2020) · Proceedings of the 2020 International Symposium on Wearable Computers

Context-Aware Activity Recognition SystemsDomain Adaptation and Few-Shot Learning

Cited by 146

Towards Deep Symbolic Reinforcement Learning

Garnelo, M., Arulkumaran, K., & Shanahan, M. (2016) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 146

Mobile Phones for Maternal Health in Rural India

Kumar, N., & Anderson, R. J. (2015) · Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

ICT in Developing CommunitiesMobile Health and mHealth Applications

Cited by 146

E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT

Poerner, N., Waltinger, U., & Schütze, H. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020

Topic ModelingMultimodal Machine Learning Applications

Cited by 146

Spatial search and the Dirac equation

Childs, A. M., & Goldstone, J. (2004) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications

Cited by 146

Iterative Wiener filters for image restoration

Hillery, A. D., & Chin, R. T. (1991) · IEEE Transactions on Signal Processing

Image and Signal Denoising MethodsAdvanced Adaptive Filtering Techniques

Cited by 146

Towards scalable bosonic quantum error correction

Terhal, B. M., Conrad, J., & Vuillot, C. (2020) · Quantum Science and Technology

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 146

Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO

Engstrom, L., Ilyas, A., Santurkar, S., Tsipras, D., Janoos, F., Rudolph, L., & Madry, A. (2020) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 146

The era of artificial intelligence deception: Unraveling the complexities of false realities and emerging threats of misinformation

Williamson, S. M., & Prybutok, V. (2024) · Information

Ethics and Social Impacts of AIMisinformation and Its Impacts

Cited by 146

Learning Performance-Improving Code Edits

Shypula, A., Madaan, A., Zeng, Y., Alon, U., Gardner, J., Hashemi, M., Neubig, G., Ranganathan, P., Bastani, O., & Yazdanbakhsh, A. (2023) · arXiv

Software Engineering ResearchParallel Computing and Optimization Techniques

Cited by 146

FEATURE-BASED FACIAL EXPRESSION RECOGNITION: SENSITIVITY ANALYSIS AND EXPERIMENTS WITH A MULTILAYER PERCEPTRON

ZHANG, Z. (1999) · International Journal of Pattern Recognition and Artificial Intelligence

Face and Expression RecognitionFace recognition and analysis

Cited by 146

Self-Supervised Learning for ECG-Based Emotion Recognition

Sarkar, P., & Etemad, A. (2020) · ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Emotion and Mood RecognitionECG Monitoring and Analysis

Cited by 146

ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing

Arawjo, I., Swoopes, C., Vaithilingam, P., Wattenberg, M., & Glassman, E. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 146