3 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
Scute: Exact Batched Serving for PEFT Adapters Beyond LoRA
Thomas Walker, Richard Baraniuk
Existing serving systems for large language models batch requests for many different LoRA adapters on one GPU. However, these systems reject adapters from other parameter-efficient…
Improving Generative Model Self-Training with Geometrically Modified Outputs
Patrick Batsell, Thomas Walker, Richard Baraniuk
Self-training generative models - the continued improvement of a model using its own outputs - is becoming increasingly important as high-quality training data becomes scarce. Howe…
Behavioral Monitoring of JEPA World Models with Jacobian Centroids
Thomas Walker, Randall Balestriero, Richard Baraniuk
Detecting failures in World Model (WM)-based planning requires monitoring whether the model is behaviorally aligned with the current task, which in turn requires studying its inter…
The Geometric Structure of Models Learning Sparse Data
Thomas Walker, T. Mitchell Roddenberry, Ahmed Imtiaz Humayun +2
The manifold hypothesis (MH) is often used to explain how machine learning can overcome the curse of dimensionality. However, the MH is only applicable in regimes where the trainin…
The Linear Centroids Hypothesis: Features as Directions Learned by Local Experts
Thomas Walker, Ahmed Imtiaz Humayun, Randall Balestriero +1
The Linear Representation Hypothesis (LRH) identifies features of a trained deep network (DN) as linear directions in the activation spaces, i.e., output spaces of intermediate lay…