1 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorization
Ryan C. Barron, Ves Grantcharov, Selma Wanna +8
Large Language Models (LLMs) are pre-trained on large-scale corpora and excel in numerous general natural language processing (NLP) tasks, such as question answering (QA). Despite…
TopicTag: Automatic Annotation of NMF Topic Models Using Chain of Thought and Prompt Tuning with LLMs
Selma Wanna, Ryan Barron, Nick Solovyev +4
Topic modeling is a technique for organizing and extracting themes from large collections of unstructured text. Non-negative matrix factorization (NMF) is a common unsupervised app…
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model Selection
Ryan Barron, Maksim E. Eren, Manish Bhattarai +3
In several Machine Learning (ML) clustering and dimensionality reduction approaches, such as non-negative matrix factorization (NMF), RESCAL, and K-Means clustering, users must sel…
Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization
Ryan Barron, Maksim E. Eren, Manish Bhattarai +6
Much of human knowledge in cybersecurity is encapsulated within the ever-growing volume of scientific papers. As this textual data continues to expand, the importance of document o…