6 citations · 10 across the 18 of their papers we have counts for
21 papers
NavBind: Diagnosing Instruction-Action Binding at Route Forks in Navigation VLAs
Josh Qixuan Sun, Xiaoying Xing, Yurun Chen +3
Vision-language-action (VLA) navigation models translate visual observations and instructions into actions. Navigation success assesses whether an agent reaches the goal. However,…
RL Teaches VLMs Where to Attend but Not How to Perceive
Ziqian Zhang, Junjie Liao, Zhining Zhang +1
Although reinforcement learning (RL) effectively trains Vision-Language Model (VLM) agents, the mechanisms behind these capability gains are poorly understood. Across four diverse…
InstanceSplat: Instance-Aware Feed-Forward 3D Gaussian Splatting for Scene Understanding
Minchao Jiang, Xiaoxuan Ma, Shunyu Jia +3
Feed-forward 3D Gaussian Splatting (3DGS) enables efficient and generalizable 3D reconstruction, but current feed-forward 3DGS methods for scene understanding remain largely catego…
Towards the Harness of Embodied Agents
Qi Wang, Tianyi Wang, Chengyang Li +6
The success of coding agents has established the harness as a paradigm: what an agent achieves depends not on the model alone, but on the infrastructure around it. We ask whether t…
Semantic Anchoring for Robotic Action Representations
Yuan Xu, Youheng Shi, Chengyang Li +2
Vision-Language-Action (VLA) models inherit rich semantic representations from pretrained Vision-Language Models, yet fine-tuning on limited robot demonstrations degrades this stru…
Resonant Minds: Closed-Loop Social Avatars with Theory of Mind
Jianxu Shangguan, Jing Xu, Hang Ye +4
Creating lifelike digital humans with genuine social intelligence requires unifying cognitive reasoning and multimodal generation within a coherent framework. Current approaches tr…
Proprioceptive-visual correspondence enables self-other distinction in humanoid robots
Yurun Chen, Tianyuan Gao, Yizhong Ge +5
Distinguishing self from others is a prerequisite for social intelligence, yet humanoid robots that increasingly share workspaces with humans still lack this ability. Here we show…
GazeVLA: Learning Human Intention for Robotic Manipulation
Chengyang Li, Kaiyi Xiong, Yuan Xu +3
Embodied foundation models have significantly propelled the advancement of artificial general intelligence, yet they rely heavily on large-scale data. Recent studies identify human…
EgoSelf: From Memory to Personalized Egocentric Assistant
Yanshuo Wang, Yuan Xu, Xuesong Li +4
Egocentric assistants often rely on first-person view data to capture user behavior and context for personalized services. Since different users exhibit distinct habits, preference…
Seeing My Future: Predicting Situated Interaction Behavior in Virtual Reality
Yuan Xu, Zimu Zhang, Xiaoxuan Ma +3
Virtual and augmented reality systems increasingly demand intelligent adaptation to user behaviors for enhanced interaction experiences. Achieving this requires accurately understa…
Embodied Representation Alignment with Mirror Neurons
Wentao Zhu, Zhining Zhang, Yuwei Ren +3
Mirror neurons are a class of neurons that activate both when an individual observes an action and when they perform the same action. This mechanism reveals a fundamental interplay…
Electromagnetic Inverse Scattering from a Single Transmitter
Yizhe Cheng, Chunxun Tian, Haoru Wang +3
Electromagnetic Inverse Scattering Problems (EISP) seek to reconstruct relative permittivity from scattered fields and are fundamental to applications like medical imaging. This in…
Learning Human-Aware Robot Policies for Adaptive Assistance
Jason Qin, Shikun Ban, Wentao Zhu +2
Developing robots that can assist humans efficiently, safely, and adaptively is crucial for real-world applications such as healthcare. While previous work often assumes a centrali…
FreeCloth: Free-form Generation Enhances Challenging Clothed Human Modeling
Hang Ye, Xiaoxuan Ma, Hai Ci +2
Achieving realistic animated human avatars requires accurate modeling of pose-dependent clothing deformations. Existing learning-based methods heavily rely on the Linear Blend Skin…
Aligning Human Motion Generation with Human Perceptions
Haoru Wang, Wentao Zhu, Luyi Miao +4
Human motion generation is a critical task with a wide range of applications. Achieving high realism in generated motions requires naturalness, smoothness, and plausibility. Despit…
Efficient Action Counting with Dynamic Queries
Xiaoxuan Ma, Zishi Li, Qiuyan Shang +4
Temporal repetition counting aims to quantify the repeated action cycles within a video. The majority of existing methods rely on the similarity correlation matrix to characterize…
Language Models Represent Beliefs of Self and Others
Wentao Zhu, Zhining Zhang, Yizhou Wang
Understanding and attributing mental states, known as Theory of Mind (ToM), emerges as a fundamental capability for human social reasoning. While Large Language Models (LLMs) appea…
Real-time Holistic Robot Pose Estimation with Unknown States
Shikun Ban, Juling Fan, Xiaoxuan Ma +3
Estimating robot pose from RGB images is a crucial problem in computer vision and robotics. While previous methods have achieved promising performance, most of them presume full kn…
Social Motion Prediction with Cognitive Hierarchies
Wentao Zhu, Jason Qin, Yuke Lou +4
Humans exhibit a remarkable capacity for anticipating the actions of others and planning their own actions accordingly. In this study, we strive to replicate this ability by addres…
ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors
Xiaoxuan Ma, Stephan P. Kaufhold, Jiajun Su +6
Understanding the behavior of non-human primates is crucial for improving animal welfare, modeling social behavior, and gaining insights into distinctively human and phylogenetical…
Human Motion Generation: A Survey
Wentao Zhu, Xiaoxuan Ma, Dongwoo Ro +6
Human motion generation aims to generate natural human pose sequences and shows immense potential for real-world applications. Substantial progress has been made recently in motion…