3 papers
cs.LG2025
Measuring Chain-of-Thought Monitorability Through Faithfulness and Verbosity
Austin Meek, Eitan Sprejer, Iván Arcuschin +2
Chain-of-thought (CoT) outputs let us read a model's step-by-step reasoning. Since any long, serial reasoning process must pass through this textual trace, the quality of the CoT i…
cs.LG2025
Convolutional Monge Mapping between EEG Datasets to Support Independent Component Labeling
Austin Meek, Carlos H. Mendoza-Cardenas, Austin J. Brockmeier
EEG recordings contain rich information about neural activity but are subject to artifacts, noise, and superficial differences due to sensors, amplifiers, and filtering. Independen…
cs.CV2025
Weakly Supervised Object Segmentation by Background Conditional Divergence
Hassan Baker, Matthew S. Emigh, Austin J. Brockmeier
As a computer vision task, automatic object segmentation remains challenging in specialized image domains without massive labeled data, such as synthetic aperture sonar images, rem…