Smyth, Padhraic

The KDD process for extracting useful knowledge from volumes of data

Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996) · Communications of the ACM

Data Mining Algorithms and ApplicationsData Mining and Machine Learning Applications

Cited by 1,934

What large language models know and what people think they know

Steyvers, M., Tejeda, H., Kumar, A., Belem, C., Karny, S., Hu, X., Mayer, L. W., & Smyth, P. (2025) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 209

Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation

Foulds, J., Boyles, L., DuBois, C., Smyth, P., & Welling, M. (2013) · Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining

Topic ModelingBayesian Methods and Mixture Models

Cited by 126

AI-Assisted Decision-making: a Cognitive Modeling Approach to Infer Latent Reliance Strategies

Tejeda, H., Kumar, A., Smyth, P., & Steyvers, M. (2022) · Computational Brain & Behavior

Human-Automation Interaction and SafetyDecision-Making and Behavioral Economics

Cited by 53

Understanding Gender Bias in AI-Generated Product Descriptions

Kelly, M., Tahaei, M., Smyth, P., & Wilcox, L. (2025) · Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency

Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection

Cited by 4

Semantic Probabilistic Control of Language Models

Ahmed, K., Belem, C. G., Smyth, P., & Singh, S. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0