most citedFALCON: Learning Force-Adaptive Humanoid Loco-Manipulation

1 citations · 1 across the 7 of their papers we have counts for

collaborators

8 papers

cs.PL2026

NoC-Out: A Formally-verified Network-on-Chip Library for Rule-based Hardware Designs

Max Kurze, František Farka, Sebastian Ertel

The Network-on-Chip (NoC) is the communication backbone of any multiprocessor chip. A failure of the NoC has severe consequences for the whole system. Yet, no approach exists that…

cs.AI2026

RoboPIN: Grounded Embodied Reasoning via Pinned Chain-of-Thought

Yaoting Huang, Yifu Yuan, Linqi Han +6

Embodied reasoning requires models to perceive task-relevant objects and spaces in physical environments and maintain consistent visual grounding throughout multi-step reasoning. H…

cs.CV2026

Hy-Embodied-VLM-1.0: Efficient Physical-World Agents

Ziyi Wang, Xumin Yu, Yongming Rao +19

Building capable embodied agents requires not only multimodal perception and understanding, but also agentic capabilities for reasoning about actions, adapting to evolving situatio…

cs.RO2026

Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models

Yifu Yuan, Yaoting Huang, Xianze Yao +20

We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied cognition, task planning, cor…

cs.RO2026

RIO: Flexible Real-Time Robot I/O for Cross-Embodiment Robot Learning

Pablo Ortega-Kral, Eliot Xing, Arthur Bucker +13

Despite recent efforts to collect multi-task, multi-embodiment datasets, to design recipes for training Vision-Language-Action models (VLAs), and to showcase these models on differ…

cs.RO2026

ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching

Shuoheng Zhang, Yifu Yuan, Hongyao Tang +7

Existing imitation learning methods enable robots to interact autonomously with the physical environment. However, contact-rich manipulation tasks remain a significant challenge du…

cs.RO2026

RPL: Learning Robust Humanoid Perceptive Locomotion on Challenging Terrains

Yuanhang Zhang, Younggyo Seo, Juyue Chen +7

Humanoid perceptive locomotion has made significant progress and shows great promise, yet achieving robust multi-directional locomotion on complex terrains remains underexplored. T…

cs.RO2025★ 1 cited

FALCON: Learning Force-Adaptive Humanoid Loco-Manipulation

Yuanhang Zhang, Yifu Yuan, Prajwal Gurunath +7

Humanoid loco-manipulation holds transformative potential for daily service and industrial tasks, yet achieving precise, robust whole-body control with 3D end-effector force intera…