14 papers
Evidence of an Emergent "Self" in Continual Robot Learning
Adidev Jhunjhunwala, Judah Goldfeder, Hod Lipson
A key challenge to understanding self-awareness has been a principled way of quantifying whether an intelligent system has a concept of a "self", and if so how to differentiate the…
Mirage Probes: How Vision Models Fake Visual Understanding
Daniel Ben-Levi, Judah Goldfeder, Weiliang Zhao +5
Vision-language models (VLMs) can answer image-based questions confidently, and often correctly, even when no image is provided. This mirage behavior inflates benchmark scores with…
Beyond Cropping and Rotation: Automated Evolution of Powerful Task-Specific Augmentations with Generative Models
Judah Goldfeder, Shreyes Kaliyur, Vaibhav Sourirajan +5
Data augmentation has long been a cornerstone for reducing overfitting in vision models, with methods like AutoAugment automating the design of task-specific augmentations. Recent…
ArticFlow: Generative Simulation of Articulated Mechanisms
Jiong Lin, Jinchen Ruan, Hod Lipson
Recent advances in generative models have produced strong results for static 3D shapes, whereas articulated 3D generation remains challenging due to action-dependent deformations a…
Accelerating scientific discovery with the common task framework
J. Nathan Kutz, Peter Battaglia, Michael Brenner +12
Machine learning (ML) and artificial intelligence (AI) algorithms are transforming and empowering the characterization and control of dynamic systems in the engineering, physical,…
Generating Auxiliary Tasks with Reinforcement Learning
Judah Goldfeder, Matthew So, Hod Lipson
Auxiliary Learning (AL) is a form of multi-task learning in which a model trains on auxiliary tasks to boost performance on a primary objective. While AL has improved generalizatio…