1 citations · 2 across the 6 of their papers we have counts for
11 papers
Historical Anchors for Scientific Forecasting on Human-Aware Knowledge Graphs
Siu Tin Wu, Ryan C. Barron, Phoebe Upton Sanderbeck +3
Predicting which scientific connections will form next can point researchers toward the most promising leads. One successful approach learns representations by sampling paths throu…
Generated Query Expansion Still Helps Strong Sparse Retrieval: A Controlled Study with SPLADE-v3
Ryan C. Barron, Cade W. Trotter, Maksim E. Eren +3
Scientific queries are often brief, while relevant papers use specialized vocabulary. Generated query expansion can bridge this mismatch, but earlier work suggests that its value s…
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…
LaFA: Latent Feature Attacks on Non-negative Matrix Factorization
Minh Vu, Ben Nebgen, Erik Skau +5
As Machine Learning (ML) applications rapidly grow, concerns about adversarial attacks compromising their reliability have gained significant attention. One unsupervised ML method…
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…
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…
Interactive Distillation of Large Single-Topic Corpora of Scientific Papers
Nicholas Solovyev, Ryan Barron, Manish Bhattarai +3
Highly specific datasets of scientific literature are important for both research and education. However, it is difficult to build such datasets at scale. A common approach is to b…
MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware
Maksim E. Eren, Manish Bhattarai, Kim Rasmussen +2
Malware is one of the most dangerous and costly cyber threats to national security and a crucial factor in modern cyber-space. However, the adoption of machine learning (ML) based…
Robust Adversarial Defense by Tensor Factorization
Manish Bhattarai, Mehmet Cagri Kaymak, Ryan Barron +3
As machine learning techniques become increasingly prevalent in data analysis, the threat of adversarial attacks has surged, necessitating robust defense mechanisms. Among these de…