34 citations · 198 across the 21 of their papers we have counts for
22 papers
Revisiting the Roles of "Text" in Text Games
Yi Gu, Shunyu Yao, Chuang Gan +2
Text games present opportunities for natural language understanding (NLU) methods to tackle reinforcement learning (RL) challenges. However, recent work has questioned the necessit…
Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation
Peihao Chen, Dongyu Ji, Kunyang Lin +4
We address a practical yet challenging problem of training robot agents to navigate in an environment following a path described by some language instructions. The instructions oft…
Learning Active Camera for Multi-Object Navigation
Peihao Chen, Dongyu Ji, Kunyang Lin +5
Getting robots to navigate to multiple objects autonomously is essential yet difficult in robot applications. One of the key challenges is how to explore environments efficiently w…
Learning Physical Dynamics with Subequivariant Graph Neural Networks
Jiaqi Han, Wenbing Huang, Hengbo Ma +3
Graph Neural Networks (GNNs) have become a prevailing tool for learning physical dynamics. However, they still encounter several challenges: 1) Physical laws abide by symmetry, whi…
Retrospectives on the Embodied AI Workshop
Matt Deitke, Dhruv Batra, Yonatan Bisk +36
We present a retrospective on the state of Embodied AI research. Our analysis focuses on 13 challenges presented at the Embodied AI Workshop at CVPR. These challenges are grouped i…
RISP: Rendering-Invariant State Predictor with Differentiable Simulation and Rendering for Cross-Domain Parameter Estimation
Pingchuan Ma, Tao Du, Joshua B. Tenenbaum +2
This work considers identifying parameters characterizing a physical system's dynamic motion directly from a video whose rendering configurations are inaccessible. Existing solutio…