Check computer science papers: citations, claims and retractions

Generation-Augmented Retrieval for Open-Domain Question Answering

Mao, Y., He, P., Liu, X., Shen, Y., Gao, J., Han, J., & Chen, W. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 146

Smiling Women Pitching Down: Auditing Representational and Presentational Gender Biases in Image Generative AI

Sun, L., Wei, M., Sun, Y., Suh, Y. J., Shen, L., & Yang, S. (2023) · Journal of Computer-Mediated Communication

Ethics and Social Impacts of AIMedia, Gender, and Advertising

Cited by 146

LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters

Chang, C., Wang, W.-Y., Peng, W.-C., & Chen, T.-F. (2023) · arXiv

Time Series Analysis and ForecastingForecasting Techniques and Applications

Cited by 146

Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detection

Wang, L., Du, L., Ye, X., Fu, Y., Guo, G., Xue, X., Feng, J., & Zhang, L. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Vision and Imaging

Cited by 146

Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT

Zhong, Q., Ding, L., Liu, J., Du, B., & Tao, D. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 146

Deep learning in robotics: survey on model structures and training strategies

Karoly, A. I., Galambos, P., Kuti, J., & Rudas, I. J. (2021) · IEEE Transactions on Systems, Man, and Cybernetics: Systems

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 146

Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs

Cai, L., Chen, Z., Luo, C., Gui, J., Ni, J., Li, D., & Chen, H. (2021) · Proceedings of the 30th ACM International Conference on Information & Knowledge Management

Advanced Graph Neural NetworksAnomaly Detection Techniques and Applications

Cited by 146

Exact Calculation of the Hessian Matrix for the Multilayer Perceptron

Bishop, C. (1992) · Neural Computation

Neural Networks and ApplicationsMachine Learning and ELM

Cited by 146

CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation

Zhang, Y., Feng, F., Zhang, J., Bao, K., Wang, Q., & He, X. (2023) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 146

How do API changes trigger stack overflow discussions? a study on the Android SDK

Linares-Vásquez, M., Bavota, G., Di Penta, M., Oliveto, R., & Poshyvanyk, D. (2014) · Proceedings of the 22nd International Conference on Program Comprehension

Software Engineering ResearchExpert finding and Q&A systems

Cited by 146

A deep auto-encoder based approach for intrusion detection system

Farahnakian, F., & Heikkonen, J. (2018) · 2018 20th International Conference on Advanced Communication Technology (ICACT)

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 146

Peer-to-peer Federated Learning on Graphs

Lalitha, A., Kilinc, O. C., Javidi, T., & Koushanfar, F. (2019) · arXiv

Privacy-Preserving Technologies in DataDistributed Control Multi-Agent Systems

Cited by 146

Ransomware Mitigation in the Modern Era: A Comprehensive Review, Research Challenges, and Future Directions

McIntosh, T., Kayes, A. S. M., Chen, Y.-P. P., Ng, A., & Watters, P. (2022) · ACM Computing Surveys

Advanced Malware Detection TechniquesSecurity and Verification in Computing

Cited by 146

Edge-Aware Guidance Fusion Network for RGB–Thermal Scene Parsing

Zhou, W., Dong, S., Xu, C., & Qian, Y. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence

Advanced Neural Network ApplicationsRemote-Sensing Image Classification

Cited by 146

Development and validation of a simulation workload measure: the simulation task load index (SIM-TLX)

Harris, D., Wilson, M., & Vine, S. (2020) · Virtual Reality

Virtual Reality Applications and ImpactsHuman-Automation Interaction and Safety

Cited by 146

Leveraging mobile phones to attain sustainable development

Rotondi, V., Kashyap, R., Pesando, L. M., Spinelli, S., & Billari, F. C. (2020) · Proceedings of the National Academy of Sciences

ICT in Developing CommunitiesEconomic Growth and Development

Cited by 146

Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

Zhang, J., Xie, R., Hou, Y., Zhao, W. X., Lin, L., & Wen, J.-R. (2023) · arXiv

Recommender Systems and TechniquesInformation Retrieval and Search Behavior

Cited by 146

Incentivizing High Quality Crowdwork

Ho, C.-J., Slivkins, A., Suri, S., & Vaughan, J. W. (2015) · Proceedings of the 24th International Conference on World Wide Web

Mobile Crowdsensing and CrowdsourcingExperimental Behavioral Economics Studies

Cited by 146

CREAT: Blockchain-Assisted Compression Algorithm of Federated Learning for Content Caching in Edge Computing

Cui, L., Su, X., Ming, Z., Chen, Z., Yang, S., Zhou, Y., & Xiao, W. (2022) · IEEE Internet of Things Journal

Caching and Content DeliveryIoT and Edge/Fog Computing

Cited by 146

A General Language Assistant as a Laboratory for Alignment

Askell, A., Bai, Y., Chen, A., Drain, D., Ganguli, D., Henighan, T., Jones, A., Joseph, N., Mann, B., DasSarma, N., et al. (2021) · arXiv

Topic ModelingEthics and Social Impacts of AI

Cited by 146

AFRL: Adaptive federated reinforcement learning for intelligent jamming defense in FANET

Mowla, N. I., Tran, N. H., Doh, I., & Chae, K. (2020) · Journal of Communications and Networks

Mobile Ad Hoc NetworksUAV Applications and Optimization

Cited by 146

Seeing Dynamic Scene in the Dark: A High-Quality Video Dataset with Mechatronic Alignment

Wang, R., Xu, X., Fu, C.-W., Lu, J., Yu, B., & Jia, J. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Image Enhancement TechniquesAdvanced Image Processing Techniques

Cited by 145

MOSDEN: An Internet of Things Middleware for Resource Constrained Mobile Devices

Perera, C., Jayaraman, P. P., Zaslavsky, A., Georgakopoulos, D., & Christen, P. (2014) · 2014 47th Hawaii International Conference on System Sciences

IoT and Edge/Fog ComputingArduino and IoT Applications

Cited by 145

Blockchain applications in the biomedical domain: A scoping review

Drosatos, G., & Kaldoudi, E. (2019) · Computational and Structural Biotechnology Journal

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 145