11 citations · 34 across the 22 of their papers we have counts for
7 papers · 1 filter
HEAL: Hierarchical Embedding Alignment Loss for Improved Retrieval and Representation Learning
Manish Bhattarai, Ryan Barron, Maksim Eren +8
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external document retrieval to provide domain-specific or up-to-date knowledge. The effect…
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…
Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with Accelerated LLMs
Afia Anjum, Maksim E. Eren, Ismael Boureima +2
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing (NLP) tasks, such as question-answering,…
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…
Catch'em all: Classification of Rare, Prominent, and Novel Malware Families
Maksim E. Eren, Ryan Barron, Manish Bhattarai +5
National security is threatened by malware, which remains one of the most dangerous and costly cyber threats. As of last year, researchers reported 1.3 billion known malware specim…