5 citations · 11 across the 11 of their papers we have counts for
8 papers · 1 filter
MolmoAct2: Action Reasoning Models for Real-world Deployment
Haoquan Fang, Jiafei Duan, Donovan Clay +26
Vision-Language-Action (VLA) models aim to provide a single generalist controller for robots, but today's systems fall short on the criteria that matter for real-world deployment.…
Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies
Yi Wang, Xinchen Li, Pengwei Xie +13
Generalist robot policies increasingly benefit from large-scale pretraining, but offline data alone is insufficient for robust real-world deployment. Deployed robots encounter dist…
RoboPlayground: Democratizing Robotic Evaluation through Structured Physical Domains
Yi Ru Wang, Carter Ung, Evan Gubarev +3
Evaluation of robotic manipulation systems has largely relied on fixed benchmarks authored by a small number of experts, where task instances, constraints, and success criteria are…
MolmoAct: Action Reasoning Models that can Reason in Space
Jason Lee, Jiafei Duan, Haoquan Fang +16
Reasoning is central to purposeful action, yet most robotic foundation models map perception and instructions directly to control, which limits adaptability, generalization, and se…
RoboEval: Where Robotic Manipulation Meets Structured and Scalable Evaluation
Yi Ru Wang, Carter Ung, Christopher Tan +11
We introduce RoboEval, a structured evaluation framework and benchmark for robotic manipulation that augments binary success with principled behavioral and outcome metrics. Existin…
SAM2Act: Integrating Visual Foundation Model with A Memory Architecture for Robotic Manipulation
Haoquan Fang, Markus Grotz, Wilbert Pumacay +4
Robotic manipulation systems operating in diverse, dynamic environments must exhibit three critical abilities: multitask interaction, generalization to unseen scenarios, and spatia…
AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation
Jiafei Duan, Wilbert Pumacay, Nishanth Kumar +7
Robotic manipulation in open-world settings requires not only task execution but also the ability to detect and learn from failures. While recent advances in vision-language models…
Manipulate-Anything: Automating Real-World Robots using Vision-Language Models
Jiafei Duan, Wentao Yuan, Wilbert Pumacay +4
Large-scale endeavors like and widespread community efforts such as Open-X-Embodiment have contributed to growing the scale of robot demonstration data. However, there is still an…