4 papers
Network of Theseus (like the ship)
Vighnesh Subramaniam, Colin Conwell, Boris Katz +2
A standard assumption in deep learning is that the inductive bias introduced by a neural network architecture must persist from training through inference. The architecture you tra…
Training the Untrainable: Introducing Inductive Bias via Representational Alignment
Vighnesh Subramaniam, David Mayo, Colin Conwell +4
We demonstrate that architectures which traditionally are considered to be ill-suited for a task can be trained using inductive biases from another architecture. We call a network…
Relations, Negations, and Numbers: Looking for Logic in Generative Text-to-Image Models
Colin Conwell, Rupert Tawiah-Quashie, Tomer Ullman
Despite remarkable progress in multi-modal AI research, there is a salient domain in which modern AI continues to lag considerably behind even human children: the reliable deployme…
Using Multimodal Deep Neural Networks to Disentangle Language from Visual Aesthetics
Colin Conwell, Christopher Hamblin, Chelsea Boccagno +4
When we experience a visual stimulus as beautiful, how much of that experience derives from perceptual computations we cannot describe versus conceptual knowledge we can readily tr…