Check computer science papers: citations, claims and retractions

Individual differences among deep neural network models

Mehrer, J., Spoerer, C. J., Kriegeskorte, N., & Kietzmann, T. C. (2020) · Nature Communications

Neural Networks and ApplicationsAdvanced Neural Network Applications

Cited by 133

A review of agent-based programming for multi-agent systems

Cardoso, R. C., & Ferrando, A. (2021) · Computers

Multi-Agent Systems and NegotiationAI-based Problem Solving and Planning

Cited by 133

Online Social Spammer Detection

Hu, X., Tang, J., & Liu, H. (2014) · Proceedings of the AAAI Conference on Artificial Intelligence

Spam and Phishing DetectionHate Speech and Cyberbullying Detection

Cited by 133

Expanding and Refining Design and Criticality in HCI

Pierce, J., Sengers, P., Hirsch, T., Jenkins, T., Gaver, W., & DiSalvo, C. (2015) · Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

Innovative Human-Technology InteractionDesign Education and Practice

Cited by 133

Sharing biodiversity data: citizen scientists’ concerns and motivations

Ganzevoort, W., van den Born, R. J. G., Halffman, W., & Turnhout, S. (2017) · Biodiversity and Conservation

Research Data Management PracticesSpecies Distribution and Climate Change

Cited by 133

Quantum Spectral Methods for Differential Equations

Childs, A. M., & Liu, J.-P. (2020) · Communications in Mathematical Physics

Quantum Computing Algorithms and ArchitectureNumerical Solvers for Ordinary Differential Equations

Cited by 133

ConvNet-Based Localization of Anatomical Structures in 3-D Medical Images

de Vos, B. D., Wolterink, J. M., de Jong, P. A., Leiner, T., Viergever, M. A., & Isgum, I. (2017) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 133

Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code

Pan, R., Ibrahimzada, A. R., Krishna, R., Sankar, D., Wassi, L. P., Merler, M., Sobolev, B., Pavuluri, R., Sinha, S., & Jabbarvand, R. (2024) · Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

Software Engineering ResearchNatural Language Processing Techniques

Cited by 133

DiffTalk: Crafting Diffusion Models for Generalized Audio-Driven Portraits Animation

Shen, S., Zhao, W., Meng, Z., Li, W., Zhu, Z., Zhou, J., & Lu, J. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 133

Learning Hidden Unit Contributions for Unsupervised Acoustic Model Adaptation

Swietojanski, P., Li, J., & Renals, S. (2016) · IEEE/ACM Transactions on Audio, Speech, and Language Processing

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 133

Natural Language Generation Using Deep Learning to Support MOOC Learners

Li, C., & Xing, W. (2021) · International Journal of Artificial Intelligence in Education

Online Learning and AnalyticsIntelligent Tutoring Systems and Adaptive Learning

Cited by 133

Towards Blended Reactive Planning and Acting using Behavior Trees

Colledanchise, M., Almeida, D., & Ogren, P. (2019) · 2019 International Conference on Robotics and Automation (ICRA)

AI-based Problem Solving and PlanningRobotic Path Planning Algorithms

Cited by 133

Adversarial Sticker: A Stealthy Attack Method in the Physical World

Wei, X., Guo, Y., & Yu, J. (2021) · arXiv

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 133

Building and Auditing Fair Algorithms: A Case Study in Candidate Screening

Wilson, C., Ghosh, A., Jiang, S., Mislove, A., Baker, L., Szary, J., Trindel, K., & Polli, F. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 133

Constrained frequent pattern mining: a pattern-growth view

Pei, J., & Han, J. (2002) · ACM SIGKDD Explorations Newsletter

Data Mining Algorithms and ApplicationsData Mining and Machine Learning Applications

Cited by 133

Event Retrieval in Large Video Collections with Circulant Temporal Encoding

Revaud, J., Douze, M., Schmid, C., & Jegou, H. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Image and Video Retrieval TechniquesVideo Analysis and Summarization

Cited by 133

On the Compatibility of Privacy and Fairness

Cummings, R., Gupta, V., Kimpara, D., & Morgenstern, J. (2019) · Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization

Privacy-Preserving Technologies in DataEthics and Social Impacts of AI

Cited by 133

Correcting Length Bias in Neural Machine Translation

Murray, K., & Chiang, D. (2018) · Proceedings of the Third Conference on Machine Translation: Research Papers

Natural Language Processing TechniquesTopic Modeling

Cited by 133

A Survey of Hallucination in Large Foundation Models

Rawte, V., Sheth, A., & Das, A. (2023) · arXiv

Topic ModelingMisinformation and Its Impacts

Cited by 133

Rotating virtual objects with real handles

Ware, C., & Rose, J. (1999) · ACM Transactions on Computer-Human Interaction

Interactive and Immersive DisplaysVirtual Reality Applications and Impacts

Cited by 133

Towards Scalable and Private Industrial Blockchains

Li, W., Sforzin, A., Fedorov, S., & Karame, G. O. (2017) · Proceedings of the ACM Workshop on Blockchain, Cryptocurrencies and Contracts

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 133

Strategic use of immersive media and narrative message in virtual marketing: Understanding the roles of telepresence and transportation

Chen, C., & Yao, M. Z. (2022) · Psychology & Marketing

Virtual Reality Applications and ImpactsMedia Influence and Health

Cited by 133

Evaluating Local Interpretable Model-Agnostic Explanations on Clinical Machine Learning Classification Models

Barr Kumarakulasinghe, N., Blomberg, T., Liu, J., Saraiva Leao, A., & Papapetrou, P. (2020) · 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 133

Fault-tolerant thresholds for quantum error correction with the surface code

Stephens, A. M. (2014) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 133