6 papers · 1 filter
MuSTMM: Learning Sound-Triggered Mobile Manipulation across Multiple Scenes
Hao Ju, Feng Yan, Zhihao Zhong +3
Sound-Triggered Mobile Manipulation (STMM) requires robots to respond to sound events by navigating to the associated objects and performing appropriate physical interactions. Exis…
Can a Frontier VLM Serve as a Robot Policy for Memory-Dependent Manipulation?
Jack B. Jedlicki, Amish Sethi, Heng Yang
We use a frozen frontier vision-language model, GPT-6-Astra, directly as the robot policy on RoboMME, a benchmark of 16 memory-dependent manipulation tasks spanning temporal, spati…
Where Memory Belongs: Ledger, an Object Ledger for Memory-Augmented VLAs
Tanguy Dieudonné, Jack B. Jedlicki, Heng Yang
Memory is essential for long-horizon, partially observed robotic manipulation: a robot must remember which object was placed in a drawer, whose cup it moved, or how many action cyc…
RoboMP-DINOv2: Prompts, Not Filters for Robust Robot Manipulation
Han Qi, Heng Yang
Robot manipulation policies must generalize across visual shifts while preserving scene context relevant to action. General-purpose vision encoders are not tailored to visuomotor c…
Towards Safe Mobility: A Unified Transportation Foundation Model enabled by Open-Ended Vision-Language Dataset
Wenhui Huang, Songyan Zhang, Collister Chua +4
Urban transportation systems face growing safety challenges that require scalable intelligence for emerging smart mobility infrastructures. While recent advances in foundation mode…
Reward Under Attack: Analyzing the Robustness and Hackability of Process Reward Models
Rishabh Tiwari, Aditya Tomar, Udbhav Bamba +5
Process Reward Models (PRMs) are rapidly becoming the backbone of LLM reasoning pipelines, yet we demonstrate that state-of-the-art PRMs are systematically exploitable under advers…