6 citations · 29 across the 17 of their papers we have counts for
4 papers · 1 filter
Traversing the solution space of neural networks with Hessian Null Space Continuation
Ann Huang, Mitchell Ostrow, Zhouyang Lu +3
On a single task, deep networks can learn many solutions, depending on their optimizer, training data, architecture, and hyperparameters. Many of these solutions are mode-connected…
Shortcut Solutions Learned by Transformers Impair Continual Compositional Reasoning
William T. Redman, Erik C. Johnson, Brian Robinson
Identifying and exploiting common features across domains is at the heart of the human ability to make analogies, and is believed to be crucial for the ability to continually learn…
Interpreting Reinforcement Learning Model Behavior via Koopman with Control
William T. Redman
Reinforcement learning (RL) models have shown the capability of learning complex behaviors, but quantitatively assessing those behaviors - which is critical for safety assurance an…
Trojans in Artificial Intelligence (TrojAI) Final Report
Kristopher W. Reese, Taylor Kulp-McDowall, Michael Majurski +68
The Intelligence Advanced Research Projects Activity (IARPA) launched the TrojAI program to confront an emerging vulnerability in modern artificial intelligence: the threat of AI T…