Check computer science papers: citations, claims and retractions

Sycophancy in Large Language Models: Causes and Mitigations

Malmqvist, L. (2024) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 95

Learning Cumulatively to Become More Knowledgeable

Fei, G., Wang, S., & Liu, B. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Domain Adaptation and Few-Shot LearningData Stream Mining Techniques

Cited by 95

Symbols and grounding in large language models

Pavlick, E. (2023) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Natural Language Processing TechniquesTopic Modeling

Cited by 95

Concept attribution: explaining cnn decisions to physicians

M., G., V., A., S., M.-M., & H., M. (2020) · Computers in Biology and Medicine

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 95

A rapid recognition method for electronic components based on the improved yolo-v3 network

Huang, R., Gu, J., Sun, X., Hou, Y., & Uddin, S. (2019) · Electronics

Advanced Neural Network ApplicationsIndustrial Vision Systems and Defect Detection

Cited by 94

AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems

Zhang, J., Hou, Y., Xie, R., Sun, W., McAuley, J., Zhao, W. X., Lin, L., & Wen, J.-R. (2024) · Proceedings of the ACM Web Conference 2024

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 94

Observation-driven geo-ontology engineering

Janowicz, K. (2012) · Transactions in GIS

Semantic Web and OntologiesGeographic Information Systems Studies

Cited by 94

Shortcut Learning of Large Language Models in Natural Language Understanding

Du, M., He, F., Zou, N., Tao, D., & Hu, X. (2024) · Communications of the ACM

Topic ModelingNatural Language Processing Techniques

Cited by 94

Learning to Calibrate Straight Lines for Fisheye Image Rectification

Xue, Z., Xue, N., Xia, G.-S., & Shen, W. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Vision and ImagingOptical measurement and interference techniques

Cited by 94

Cross-cultural and cultural-specific production and perception of facial expressions of emotion in the wild

Srinivasan, R., & Martinez, A. M. (2021) · IEEE Transactions on Affective Computing

Emotion and Mood RecognitionFace Recognition and Perception

Cited by 94

Cosmo: contrastive fusion learning with small data for multimodal human activity recognition

Ouyang, X., Shuai, X., Zhou, J., Shi, I. W., Xie, Z., Xing, G., & Huang, J. (2022) · Proceedings of the 28th Annual International Conference on Mobile Computing And Networking

Context-Aware Activity Recognition SystemsIoT and Edge/Fog Computing

Cited by 94

Color Image Encryption Algorithm Based on DNA Coding and Double Chaos System

Liu, Q., & Liu, L. (2020) · IEEE Access

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 94

Improving Data Quality Using Amazon Mechanical Turk Through Platform Setup

Lu, L., Neale, N., Line, N. D., & Bonn, M. (2022) · Cornell Hospitality Quarterly

Mobile Crowdsensing and CrowdsourcingSurvey Methodology and Nonresponse

Cited by 94

Gaussian states of continuous-variable quantum systems provide universal and versatile reservoir computing

Nokkala, J., Martínez-Peña, R., Giorgi, G. L., Parigi, V., Soriano, M. C., & Zambrini, R. (2020) · arXiv

Neural Networks and Reservoir ComputingQuantum Computing Algorithms and Architecture

Cited by 94

Modeling Heart Rate and Activity Data for Personalized Fitness Recommendation

Ni, J., Muhlstein, L., & McAuley, J. (2019) · The World Wide Web Conference

Context-Aware Activity Recognition SystemsRecommender Systems and Techniques

Cited by 94

Once for All: A Two-Flow Convolutional Neural Network for Visual Tracking

Chen, K., & Tao, W. (2018) · IEEE Transactions on Circuits and Systems for Video Technology

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 94

Artificial intelligence and climate change: ethical issues

Nordgren, A. (2023) · Journal of Information, Communication and Ethics in Society

Ethics and Social Impacts of AIInnovation, Sustainability, Human-Machine Systems

Cited by 94

Baldur: Whole-Proof Generation and Repair with Large Language Models

First, E., Rabe, M. N., Ringer, T., & Brun, Y. (2023) · Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Logic, programming, and type systemsFormal Methods in Verification

Cited by 94

Qwen2.5-VL Technical Report

Bai, S., Chen, K., Liu, X., Wang, J., Ge, W., Song, S., Dang, K., Wang, P., Wang, S., Tang, J., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 94

Cyberbullying Detection: An Ensemble Based Machine Learning Approach

Alam, K. S., Bhowmik, S., & Prosun, P. R. K. (2021) · 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV)

Hate Speech and Cyberbullying DetectionText and Document Classification Technologies

Cited by 94

Permanents in linear optical networks

Scheel, S. (2004) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 94

AI, Opacity, and Personal Autonomy

Vaassen, B. (2022) · Philosophy & Technology

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 94

A Deep CNN-Based Framework For Enhanced Aerial Imagery Registration with Applications to UAV Geolocalization

Nassar, A., Amer, K., ElHakim, R., & ElHelw, M. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Advanced Image and Video Retrieval TechniquesRobotics and Sensor-Based Localization

Cited by 94

Automatic Detection and Segmentation of Lymph Nodes From CT Data

Barbu, A., Suehling, M., Xu, X., Liu, D., Zhou, S. K., & Comaniciu, D. (2012) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesAI in cancer detection

Cited by 94