activity
20242026
collaborators

11 papers

cs.RO2026

RoboIRS: Inference-Time Internal Representation Steering for Generalist Robot Policies

Jiuzhou Lei, Chang Liu, Dayou Li +5

Vision-language-action (VLA) and world-action models (WAMs) often degrade under out-of-distribution task variations despite retaining partial task capability. To recover such capab…

cs.RO2026

PHR-VLA: Planning Horizon Reasoning for Vision-Language-Action Models

Davood Soleymanzadeh, Kaidi Zhang, Zhiyuan Zhang +4

Vision-language-action models (VLAs) have shown strong promise for general-purpose robotic manipulation by mapping language instructions and vision observations directly to actions…

cs.RO2026

Imagining the Sense of Touch: Touch-Informed Manipulation via Imagined Tactile Representations

Zhiyuan Zhang, Adeesh Desai, Jyun-Chi Hu +7

Tactile sensing can substantially improve contact-rich robotic manipulation, yet its practical deployment remains limited by the fragility, calibration requirements, and maintenanc…

cs.RO2026

DREAM-Chunk: Reactive Action Chunking with Latent World Model

Wenxi Chen, Kaidi Zhang, Chi Lin +6

Action chunking has become a common interface for vision-language-action (VLA) models, enabling low-frequency policy inference to drive high-frequency robot execution. However, onc…

cs.RO2026

ReactSim-Bench: Benchmarking Reactive Behavior World Model Simulation in Autonomous Driving

Zhiyuan Zhang, Yanlun Peng, Jianing Zhang +7

Reactive capability is a key property of data-driven behavior world model simulators for autonomous driving simulation systems. With this capability, simulated world agents can res…

cs.RO2026

ContactWorld: What Representations Matter for Vision-Tactile Latent World Models in Contact-Rich Manipulation

Zhiyuan Zhang, Pokuang Zhou, Kaidi Zhang +7

Contact-rich manipulation poses a fundamental challenge for world models: visual and tactile observations capture different aspects of physical interaction, and their utility depen…

cs.RO2026

TacVLA: Contact-Aware Tactile Fusion for Robust Vision-Language-Action Manipulation

Kaidi Zhang, Heng Zhang, Zhengtong Xu +7

Vision-Language-Action (VLA) models have demonstrated significant advantages in robotic manipulation. However, their reliance on vision and language often leads to suboptimal perfo…

cs.RO2026

CONTACT: CONtact-aware TACTile Learning for Robotic Disassembly

Yosuke Saka, Jyun-Chi Hu, Adeesh Desai +6

Robotic disassembly involves contact-rich interactions in which successful manipulation depends not only on geometric alignment but also on force-dependent state transitions. While…

cs.RO2026

EquiBim: Learning Symmetry-Equivariant Policy for Bimanual Manipulation

Zhiyuan Zhang, Aditya Mohan, Seungho Han +3

Robotic imitation learning has achieved impressive success in learning complex manipulation behaviors from demonstrations. However, many existing robot learning methods do not expl…

cs.GR2025

Learned Adaptive Mesh Generation

Zhiyuan Zhang, Amir Vaxman, Stefanos-Aldo Papanicolopulos +1

Elliptic Partial Differential Equations (PDEs) play a central role in computing the equilibrium conditions of physical problems (heat, gravitation, electrostatics, etc.). Efficient…

cs.GR2024

Implicit-Explicit simulation of Mass-Spring-Charge Systems

Zhiyuan Zhang, Krzysztof Grykiel, Zhaocheng Liu +2

Point masses connected by springs, or mass-spring systems, are widely used in computer animation to approximate the behavior of deformable objects. One of the restrictions imposed…