21 citations · 32 across the 12 of their papers we have counts for
5 papers · 1 filter
Open Vocabulary Compositional Explanations for Neuron Alignment
Biagio La Rosa, Leilani H. Gilpin
Neurons are the fundamental building blocks of deep neural networks, and their interconnections allow AI to achieve unprecedented results. Motivated by the goal of understanding ho…
Guaranteed Optimal Compositional Explanations for Neurons
Biagio La Rosa, Leilani H. Gilpin
Compositional explanations are a family of methods that aim to describe the spatial alignment between neurons' receptive field activations and concepts through logical rules, typic…
Follow My Lead: Logical Fallacy Classification with Knowledge-Augmented LLMs
Olivia Peiyu Wang, Tashvi Bansal, Ryan Bai +2
Large Language Models (LLMs) suffer from critical reasoning gaps, including a tendency to hallucinate and poor accuracy in classifying logical fallacies. This limitation stems from…
Explore the Loss space with Hill-ADAM
Meenakshi Manikandan, Leilani Gilpin
This paper introduces Hill-ADAM. Hill-ADAM is an optimizer with its focus towards escaping local minima in prescribed loss landscapes to find the global minimum. Hill-ADAM escapes…
VFSI: Validity First Spatial Intelligence for Constraint-Guided Traffic Diffusion
Kargi Chauhan, Leilani H. Gilpin
Modern diffusion models generate realistic traffic simulations but systematically violate physical constraints. In a large-scale evaluation of SceneDiffuser++, a state-of-the-art t…