6 citations · 20 across the 14 of their papers we have counts for
13 papers
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…
Learning to Act from Actionless Videos through Dense Correspondences
Po-Chen Ko, Jiayuan Mao, Yilun Du +2
In this work, we present an approach to construct a video-based robot policy capable of reliably executing diverse tasks across different robots and environments from few video dem…
HandMeThat: Human-Robot Communication in Physical and Social Environments
Yanming Wan, Jiayuan Mao, Joshua B. Tenenbaum
We introduce HandMeThat, a benchmark for a holistic evaluation of instruction understanding and following in physical and social environments. While previous datasets primarily foc…
Compositional Diffusion-Based Continuous Constraint Solvers
Zhutian Yang, Jiayuan Mao, Yilun Du +4
This paper introduces an approach for learning to solve continuous constraint satisfaction problems (CCSP) in robotic reasoning and planning. Previous methods primarily rely on han…
Programmatically Grounded, Compositionally Generalizable Robotic Manipulation
Renhao Wang, Jiayuan Mao, Joy Hsu +3
Robots operating in the real world require both rich manipulation skills as well as the ability to semantically reason about when to apply those skills. Towards this goal, recent w…