1 citations · 2 across the 14 of their papers we have counts for
15 papers
The Human--VLA Communication Gap: What Humans Leave Implicit and What Policies Cannot Recover
Yiqing Xu, Jiajun Wu
A robot may know how to perform a task yet fail when a human asks for it naturally. We study this human--VLA communication gap by separating an \emph{information gap}, where task s…
APIVOT: Adaptive Planning with Interleaved Vision-Language Thoughts
Emily Jin, Joy Hsu, Yiqing Xu +3
Long-horizon robot planning requires jointly reasoning over semantic task structure and geometric feasibility. To successfully execute a task, a robot must decompose goals, select…
VLS: Steering Pretrained Robot Policies via Vision-Language Models
Shuo Liu, Ishneet Sukhvinder Singh, Yiqing Xu +2
Why do pretrained diffusion or flow-matching policies fail when the same task is performed near an obstacle, on a shifted support surface, or amid mild clutter? Such failures rarel…
"Set It Up": Functional Object Arrangement with Compositional Generative Models (Journal Version)
Yiqing Xu, Jiayuan Mao, Linfeng Li +4
Functional object arrangement (FORM) is the task of arranging objects to fulfill a function, e.g., "set up a dining table for two". One key challenge here is that the instructions…
"Stack It Up!": 3D Stable Structure Generation from 2D Hand-drawn Sketch
Yiqing Xu, Linfeng Li, Cunjun Yu +1
Imagine a child sketching the Eiffel Tower and asking a robot to bring it to life. Today's robot manipulation systems can't act on such sketches directly-they require precise 3D bl…
Differentiable Particles for General-Purpose Deformable Object Manipulation
Siwei Chen, Yiqing Xu, Cunjun Yu +2
Deformable object manipulation is a long-standing challenge in robotics. While existing approaches often focus narrowly on a specific type of object, we seek a general-purpose algo…
"Set It Up!": Functional Object Arrangement with Compositional Generative Models
Yiqing Xu, Jiayuan Mao, Yilun Du +3
This paper studies the challenge of developing robots capable of understanding under-specified instructions for creating functional object arrangements, such as "set up a dining ta…
LLMs for Robotic Object Disambiguation
Connie Jiang, Yiqing Xu, David Hsu
The advantages of pre-trained large language models (LLMs) are apparent in a variety of language processing tasks. But can a language model's knowledge be further harnessed to effe…
Learning Reward for Physical Skills using Large Language Model
Yuwei Zeng, Yiqing Xu
Learning reward functions for physical skills are challenging due to the vast spectrum of skills, the high-dimensionality of state and action space, and nuanced sensory feedback. T…
"Tidy Up the Table": Grounding Common-sense Objective for Tabletop Object Rearrangement
Yiqing Xu, David Hsu
Tidying up a messy table may appear simple for humans, but articulating clear criteria for tidiness is challenging due to the ambiguous nature of common sense reasoning. Large Lang…
On the Effective Horizon of Inverse Reinforcement Learning
Yiqing Xu, Finale Doshi-Velez, David Hsu
Inverse reinforcement learning (IRL) algorithms often rely on (forward) reinforcement learning or planning, over a given time horizon, to compute an approximately optimal policy fo…
COACH: Cooperative Robot Teaching
Cunjun Yu, Yiqing Xu, Linfeng Li +1
Knowledge and skills can transfer from human teachers to human students. However, such direct transfer is often not scalable for physical tasks, as they require one-to-one interact…
DaXBench: Benchmarking Deformable Object Manipulation with Differentiable Physics
Siwei Chen, Yiqing Xu, Cunjun Yu +4
Deformable Object Manipulation (DOM) is of significant importance to both daily and industrial applications. Recent successes in differentiable physics simulators allow learning al…
Receding Horizon Inverse Reinforcement Learning
Yiqing Xu, Wei Gao, David Hsu
Inverse reinforcement learning (IRL) seeks to infer a cost function that explains the underlying goals and preferences of expert demonstrations. This paper presents receding horizo…
Factor Graph Molecule Network for Structure Elucidation
Hieu Le Trung, Yiqing Xu, Wee Sun Lee
Designing a network to learn a molecule structure given its physical/chemical properties is a hard problem, but is useful for drug discovery tasks. In this paper, we incorporate hi…