Check computer science papers: citations, claims and retractions

Explainable artificial intelligence for digital forensics

Hall, S. W., Sakzad, A., & Choo, K. R. (2022) · WIREs Forensic Science

Digital and Cyber ForensicsExplainable Artificial Intelligence (XAI)

Cited by 66

Semi-Cyclic Stochastic Gradient Descent

Eichner, H., Koren, T., McMahan, H. B., Srebro, N., & Talwar, K. (2019) · arXiv

Stochastic Gradient Optimization TechniquesPrivacy-Preserving Technologies in Data

Cited by 66

Adaptable butterfly accelerator for attention-based NNs via hardware and algorithm co-design

Fan, H., Chau, T., Venieris, S. I., Lee, R., Kouris, A., Luk, W., Lane, N. D., & Abdelfattah, M. S. (2022) · 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO)

Advanced Neural Network ApplicationsEmbedded Systems Design Techniques

Cited by 66

Keeping Your Readers' Eyes on the Screen: An Eye-Tracking Study Comparing Sans Serif and Serif Typefaces

Josephson, S. (2008) · Visual Communication Quarterly

Gaze Tracking and Assistive TechnologyGraphic Design and Typography

Cited by 66

ChatGPT as Research Scientist: Probing GPT’s capabilities as a Research Librarian, Research Ethicist, Data Generator, and Data Predictor

Lehr, S. A., Caliskan, A., Liyanage, S., & Banaji, M. R. (2024) · Proceedings of the National Academy of Sciences

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 66

The Ethical Challenges of Publishing Twitter Data for Research Dissemination

Webb, H., Jirotka, M., Stahl, B. C., Housley, W., Edwards, A., Williams, M., Procter, R., Rana, O., & Burnap, P. (2017) · Proceedings of the 2017 ACM on Web Science Conference

Ethics and Social Impacts of AIFocus Groups and Qualitative Methods

Cited by 66

On scalable oversight with weak LLMs judging strong LLMs

Kenton, Z., Siegel, N. Y., Kramár, J., Brown-Cohen, J., Albanie, S., Bulian, J., Agarwal, R., Lindner, D., Tang, Y., Goodman, N. D., et al. (2024) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 66

Software plagiarism detection: a graph-based approach

Chae, D.-K., Ha, J., Kim, S.-W., Kang, B., & Im, E. G. (2013) · Proceedings of the 22nd ACM international conference on Information & Knowledge Management

Software Engineering ResearchAcademic integrity and plagiarism

Cited by 66

Editing Models with Task Arithmetic

Ilharco, G., Ribeiro, M. T., Wortsman, M., Gururangan, S., Schmidt, L., Hajishirzi, H., & Farhadi, A. (2022) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 66

What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

Mandlekar, A., Xu, D., Wong, J., Nasiriany, S., Wang, C., Kulkarni, R., Fei-Fei, L., Savarese, S., Zhu, Y., & Martín-Martín, R. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 66

Hi YouTube!: personality impressions and verbal content in social video

Biel, J.-I., Tsiminaki, V., Dines, J., & Gatica-Perez, D. (2013) · Proceedings of the 15th ACM on International conference on multimodal interaction

Emotion and Mood RecognitionPersonality Traits and Psychology

Cited by 66

The Next Generation of Medical Decision Support: A Roadmap Toward Transparent Expert Companions

Bruckert, S., Finzel, B., & Schmid, U. (2020) · Frontiers in Artificial Intelligence

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

Cited by 66

A machine learning approach to live migration modeling

Jo, C., Cho, Y., & Egger, B. (2017) · Proceedings of the 2017 Symposium on Cloud Computing

Cloud Computing and Resource ManagementEnergy Efficiency in Computing

Cited by 66

Attention-Based Multimodal Fusion with Contrast for Robust Clinical Prediction in the Face of Missing Modalities

Liu, J., Capurro, D., Nguyen, A., & Verspoor, K. (2023) · Journal of Biomedical Informatics

Machine Learning in HealthcareMultimodal Machine Learning Applications

Cited by 66

AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers

Faraone, J., Kumm, M., Hardieck, M., Zipf, P., Liu, X., Boland, D., & Leong, P. H. W. (2020) · IEEE Transactions on Very Large Scale Integration (VLSI) Systems

Advanced Neural Network ApplicationsEmbedded Systems Design Techniques

Cited by 66

What matters when building vision-language models?

Laurençon, H., Tronchon, L., Cord, M., & Sanh, V. (2024) · Advances in Neural Information Processing Systems 37

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 66

Deep Learning for Handling Kernel/model Uncertainty in Image Deconvolution

Nan, Y., & Ji, H. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Image Processing TechniquesImage and Signal Denoising Methods

Cited by 66

Big(ger) data as better data in open distance learning

Prinsloo, P., Archer, E., Barnes, G., Chetty, Y., & Van Zyl, D. (2015) · The International Review of Research in Open and Distributed Learning

Online Learning and AnalyticsBig Data Technologies and Applications

Cited by 66

Spectro-temporal analysis of speech using 2-d Gabor filters

Ezzat, T., Bouvrie, J., & Poggio, T. (2007) · Interspeech 2007

Speech and Audio ProcessingSpeech Recognition and Synthesis

Cited by 66

Spreading vectors for similarity search

Sablayrolles, A., Douze, M., Schmid, C., & Jégou, H. (2018) · arXiv

Advanced Image and Video Retrieval TechniquesAdvanced Clustering Algorithms Research

Cited by 66

An Empirical Study on Culture, Automation, Measurement, and Sharing of DevSecOps

Tomas, N., Li, J., & Huang, H. (2019) · 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security)

Software Engineering Techniques and PracticesWeb Application Security Vulnerabilities

Cited by 66

Hash Layers For Large Sparse Models

Roller, S., Sukhbaatar, S., Szlam, A., & Weston, J. (2021) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 66

Programming education and learner motivation in the age of generative AI: student and educator perspectives

Boguslawski, S., Deer, R., & Dawson, M. G. (2025) · Information and Learning Sciences

Teaching and Learning ProgrammingArtificial Intelligence in Education

Cited by 66

Scaling of variational quantum circuit depth for condensed matter systems

Bravo-Prieto, C., Lumbreras-Zarapico, J., Tagliacozzo, L., & Latorre, J. I. (2020) · Quantum

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 66