4 papers
ConceptTracer: Interactive Analysis of Concept Saliency and Selectivity in Neural Representations
Ricardo Knauer, Andre Beinrucker, Erik Rodner
Neural networks deliver impressive predictive performance across a variety of tasks, but they are often opaque in their decision-making processes. Despite a growing interest in mec…
Embedding World Knowledge into Tabular Models: Towards Best Practices for Embedding Pipeline Design
Oksana Kolomenko, Ricardo Knauer, Erik Rodner
Embeddings are a powerful way to enrich data-driven machine learning models with the world knowledge of large language models (LLMs). Yet, there is limited evidence on how to desig…
In Search of Grandmother Cells: Tracing Interpretable Neurons in Tabular Representations
Ricardo Knauer, Erik Rodner
Foundation models are powerful yet often opaque in their decision-making. A topic of continued interest in both neuroscience and artificial intelligence is whether some neurons beh…
"Oh LLM, I'm Asking Thee, Please Give Me a Decision Tree": Zero-Shot Decision Tree Induction and Embedding with Large Language Models
Ricardo Knauer, Mario Koddenbrock, Raphael Wallsberger +5
Large language models (LLMs) provide powerful means to leverage prior knowledge for predictive modeling when data is limited. In this work, we demonstrate how LLMs can use their co…