35 citations · 71 across the 23 of their papers we have counts for
10 papers · 1 filter
Bayes3D: fast learning and inference in structured generative models of 3D objects and scenes
Nishad Gothoskar, Matin Ghavami, Eric Li +8
Robots cannot yet match humans' ability to rapidly learn the shapes of novel 3D objects and recognize them robustly despite clutter and occlusion. We present Bayes3D, an uncertaint…
Learning adaptive planning representations with natural language guidance
Lionel Wong, Jiayuan Mao, Pratyusha Sharma +5
Effective planning in the real world requires not only world knowledge, but the ability to leverage that knowledge to build the right representation of the task at hand. Decades of…
How to guess a gradient
Utkarsh Singhal, Brian Cheung, Kartik Chandra +4
How much can you say about the gradient of a neural network without computing a loss or knowing the label? This may sound like a strange question: surely the answer is "very little…
What Planning Problems Can A Relational Neural Network Solve?
Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum +1
Goal-conditioned policies are generally understood to be "feed-forward" circuits, in the form of neural networks that map from the current state and the goal specification to the n…
Learning Reusable Manipulation Strategies
Jiayuan Mao, Joshua B. Tenenbaum, Tomás Lozano-Pérez +1
Humans demonstrate an impressive ability to acquire and generalize manipulation "tricks." Even from a single demonstration, such as using soup ladles to reach for distant objects,…
What's Left? Concept Grounding with Logic-Enhanced Foundation Models
Joy Hsu, Jiayuan Mao, Joshua B. Tenenbaum +1
Recent works such as VisProg and ViperGPT have smartly composed foundation models for visual reasoning-using large language models (LLMs) to produce programs that can be executed b…
AI for Mathematics: A Cognitive Science Perspective
Cedegao E. Zhang, Katherine M. Collins, Adrian Weller +1
Mathematics is one of the most powerful conceptual systems developed and used by the human species. Dreams of automated mathematicians have a storied history in artificial intellig…
LILO: Learning Interpretable Libraries by Compressing and Documenting Code
Gabriel Grand, Lionel Wong, Maddy Bowers +4
While large language models (LLMs) now excel at code generation, a key aspect of software development is the art of refactoring: consolidating code into libraries of reusable and r…
Getting aligned on representational alignment
Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller +30
Biological and artificial information processing systems form representations of the world that they can use to categorize, reason, plan, navigate, and make decisions. How can we m…
ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning
Qiao Gu, Alihusein Kuwajerwala, Sacha Morin +13
For robots to perform a wide variety of tasks, they require a 3D representation of the world that is semantically rich, yet compact and efficient for task-driven perception and pla…