activity
20232026
most citedChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors

6 citations · 10 across the 19 of their papers we have counts for

collaborators

21 papers

cs.RO2026

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…

cs.RO2026

WAM-TTT: Steering World-Action Models by Watching Human Play at Test Time

Yusen Feng, Bingchen Han, Jiangran Lyu +13

Steering robot foundation models (RFMs) toward new task variants or user-preferred behaviors remains challenging, often requiring additional robot demonstrations, task-specific fin…

cs.CV2026

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…

cs.CV2026

MUSE: A Unified Agentic Harness for MLLMs

Jianglin Lu, Hailing Wang, Xu Ma +4

Despite rapid progress, multimodal large language models (MLLMs) still fail on tasks that humans solve effortlessly, such as navigating a grid maze from a screenshot or selecting t…

cs.RO2026

GazeVLA: Learning Human Intention for Robotic Manipulation

Chengyang Li, Kaiyi Xiong, Yuan Xu +3

Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstrations. Although recent works…

cs.CV2026

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…

cs.CL2026

Neural Synchrony Between Socially Interacting Language Models

Zhining Zhang, Wentao Zhu, Chi Han +2

Neuroscience has uncovered a fundamental mechanism of our social nature: human brain activity becomes synchronized with others in many social contexts involving interaction. Tradit…

cs.CV2025

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…

cs.AI2025

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…

cs.CV2025

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…

cs.RO2024

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…

cs.CV2024

AlphaChimp: Tracking and Behavior Recognition of Chimpanzees

Xiaoxuan Ma, Yutang Lin, Yuan Xu +6

Understanding non-human primate behavior is crucial for improving animal welfare, modeling social behavior, and gaining insights into both distinctly human and shared behaviors. De…

cs.CV2024

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…

cs.CV2024

SAT-HMR: Real-Time Multi-Person 3D Mesh Estimation via Scale-Adaptive Tokens

Chi Su, Xiaoxuan Ma, Jiajun Su +1

We propose a one-stage framework for real-time multi-person 3D human mesh estimation from a single RGB image. While current one-stage methods, which follow a DETR-style pipeline, a…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.AI2024★ 1 cited

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…

cs.CV2024★ 1 cited

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…

cs.CV2023

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…

cs.CV2023★ 6 cited

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…

cs.CV2023★ 1 cited

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…