1 citations · 1 across the 15 of their papers we have counts for
17 papers
ECHO: Embodied Camera Observations of Human Object Carrying
Xuefei Sun, Lorin Achey, Kali Hamilton +4
Embodied and assistive agents must do more than recognize objects: they must reason about where an object belongs given the layout of an environment and the habits of the people wh…
Contextual Observer Grounding: Evaluating Situated Spatial Reasoning in Vision-Language Models
Mimo Shirasaka, Haochen Zhang, Yonatan Bisk
Reasoning over language instructions in embodied tasks such as robotics often requires understanding spatial relations from a speaker's situated perspective. Humans infer such pers…
Lost in Reconstruction: Aligning Action Representations with Language in Vision-Language-Action Models
Li Wenjie, Yash Jangir, Ignacy Stepka +3
Action verbs describe not only the physical outcomes of actions, but also how those actions are performed. Yet action representations in vision-language-action models (VLAs) are ty…
ELASTIC: Efficiently Learning to Adaptively Scale Test-Time Compute for Generative Control Policies
Andrew Zou Li, Gokul Swamy, Yonatan Bisk +1
Generative control policies (GCPs), such as diffusion policies and flow-based vision-language-action models, enable test-time scaling in robot control. Test-time compute can be all…
Flatness Preserves Instruction Following in Vision-Language-Action Models
Haochen Zhang, Yonatan Bisk
Vision-language-action (VLA) models have the potential for open-world generalization by leveraging pretrained vision-language representations, yet downstream finetuning on limited…
Inductive Generalization for Robotic Manipulation
Annabella Macaluso, Haochen Zhang, Ishaan Masilamony +2
Understanding the generalization capabilities of visuomotor policies is essential in the development of capable robotic agents. Generalizable models learn structures that transfer…
Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment
Jared Fernandez, Clara Na, Yonatan Bisk +2
Proper accounting of the energy requirements and environmental impact of artificial intelligence (AI) systems is necessary for researchers, developers, policy makers, and users to…
Public Perceptions and Acceptance of Socially Intelligent AI Agents
Leena Mathur, Jenny T. Liang, Vasudha Varadarajan +6
AI researchers have been advancing socially intelligent AI agents (Social-AI) across embodiments, from chatbots to physical robots. As Social-AI agents move from labs into everyday…
On Safety Risks in Experience-Driven Self-Evolving Agents
Weixiang Zhao, Yichen Zhang, Yingshuo Wang +8
Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduc…
IndoorR2X: Indoor Robot-to-Everything Coordination with LLM-Driven Planning
Fan Yang, Soumya Teotia, Shaunak A. Mehta +8
Although robot-to-robot (R2R) communication improves indoor scene understanding beyond what a single robot can achieve, R2R alone cannot overcome partial observability without subs…
Affordance RAG: Hierarchical Multimodal Retrieval with Affordance-Aware Embodied Memory for Mobile Manipulation
Ryosuke Korekata, Quanting Xie, Yonatan Bisk +1
In this study, we address the problem of open-vocabulary mobile manipulation, where a robot is required to carry a wide range of objects to receptacles based on free-form natural l…
REM: Evaluating LLM Embodied Spatial Reasoning through Multi-Frame Trajectories
Jacob Thompson, Emiliano Garcia-Lopez, Yonatan Bisk
Humans build viewpoint-independent cognitive maps through navigation, enabling intuitive reasoning about object permanence and spatial relations. We argue that multimodal large lan…
MolErr2Fix: Benchmarking LLM Trustworthiness in Chemistry via Modular Error Detection, Localization, Explanation, and Revision
Yuyang Wu, Jinhui Ye, Shuhao Zhang +3
Large Language Models (LLMs) have shown growing potential in molecular sciences, but they often produce chemically inaccurate descriptions and struggle to recognize or justify pote…
RobotArena : Scalable Robot Benchmarking via Real-to-Sim Translation
Yash Jangir, Yidi Zhang, Pang-Chi Lo +7
The pursuit of robot generalists, agents capable of performing diverse tasks across diverse environments, demands rigorous and scalable evaluation. Yet real-world testing of robot…
RAVEN: Resilient Aerial Navigation via Open-Set Semantic Memory and Behavior Adaptation
Seungchan Kim, Omar Alama, Dmytro Kurdydyk +5
Aerial outdoor semantic navigation requires robots to explore large, unstructured environments to locate target objects. Recent advances in semantic navigation have demonstrated op…
Towards Embodiment Scaling Laws in Robot Locomotion
Bo Ai, Liu Dai, Nico Bohlinger +7
Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…