17 citations · 18 across the 14 of their papers we have counts for
16 papers
LLM-as-a-Verifier: A General-Purpose Verification Framework
Jacky Kwok, Shulu Li, Pranav Atreya +6
Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we identify verification, the abi…
Constrained Whole-Body Tracking for Humanoid Robots
Daniel Morton, Pranit Mohnot, Marco Pavone
Recent advances in reinforcement learning (RL) have demonstrated impressive whole-body agility for humanoid robots, yet ensuring safety and satisfying constraints -- particularly t…
StressDream: Steering Video World Models for Robust Policy Evaluation and Improvement
Junwon Seo, Sushant Veer, Ran Tian +6
Video world models (WMs) have shown promise for policy evaluation and improvement by imagining realistic future observations conditioned on ego-robot actions. While WMs can model d…
Observing and Controlling Features in Vision-Language-Action Models
Hugo Buurmeijer, Carmen Amo Alonso, Aiden Swann +1
Vision-Language-Action models (VLAs) have shown remarkable progress towards embodied intelligence. While their architecture partially resembles that of Large Language Models (LLMs)…
Scaling Verification Can Be More Effective than Scaling Policy Learning for Vision-Language-Action Alignment
Jacky Kwok, Xilun Zhang, Mengdi Xu +4
The long-standing vision of general-purpose robots hinges on their ability to understand and act upon natural language instructions. Vision-Language-Action (VLA) models have made r…
Self-Supervised Bootstrapping of Action-Predictive Embodied Reasoning
Milan Ganai, Katie Luo, Jonas Frey +2
Embodied Chain-of-Thought (CoT) reasoning has significantly enhanced Vision-Language-Action (VLA) models, yet current methods rely on rigid templates to specify reasoning primitive…
Foundation models on the bridge: Semantic hazard detection and safety maneuvers for maritime autonomy with vision-language models
Kim Alexander Christensen, Andreas Gudahl Tufte, Alexey Gusev +5
The draft IMO MASS Code requires autonomous and remotely supervised maritime vessels to detect departures from their operational design domain, enter a predefined fallback that not…
RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models
Jacky Kwok, Christopher Agia, Rohan Sinha +5
Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in visuomotor control, yet ensuring their robustness in unstructured real-world environments remains a…
ARMOR: Aligning Secure and Safe Large Language Models via Meticulous Reasoning
Zhengyue Zhao, Yingzi Ma, Somesh Jha +3
Large Language Models have shown impressive generative capabilities across diverse tasks, but their safety remains a critical concern. Existing post-training alignment methods, suc…
CUPID: Curating Data your Robot Loves with Influence Functions
Christopher Agia, Rohan Sinha, Jingyun Yang +5
In robot imitation learning, policy performance is tightly coupled with the quality and composition of the demonstration data. Yet, developing a precise understanding of how indivi…
Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis
Yuan Gao, Mattia Piccinini, Yuchen Zhang +12
For autonomous vehicles, safe navigation in complex environments depends on handling a broad range of diverse and rare driving scenarios. Simulation- and scenario-based testing hav…
Scan, Materialize, Simulate: A Generalizable Framework for Physically Grounded Robot Planning
Amine Elhafsi, Daniel Morton, Marco Pavone
Autonomous robots must reason about the physical consequences of their actions to operate effectively in unstructured, real-world environments. We present Scan, Materialize, Simula…
Deformable Cargo Transport in Microgravity with Astrobee
Daniel Morton, Rika Antonova, Brian Coltin +2
We present pyastrobee: a simulation environment and control stack for Astrobee in Python, with an emphasis on cargo manipulation and transport tasks. We also demonstrate preliminar…
Real-Time Out-of-Distribution Failure Prevention via Multi-Modal Reasoning
Milan Ganai, Rohan Sinha, Christopher Agia +3
While foundation models offer promise toward improving robot safety in out-of-distribution (OOD) scenarios, how to effectively harness their generalist knowledge for real-time, dyn…
Deep Learning Warm Starts for Trajectory Optimization on the International Space Station
Somrita Banerjee, Abhishek Cauligi, Marco Pavone
Trajectory optimization is a cornerstone of modern robot autonomy, enabling systems to compute trajectories and controls in real-time while respecting safety and physical constrain…
Safe, Task-Consistent Manipulation with Operational Space Control Barrier Functions
Daniel Morton, Marco Pavone
Safe real-time control of robotic manipulators in unstructured environments requires handling numerous safety constraints without compromising task performance. Traditional approac…