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20222026
most citedGemini Robotics: Bringing AI into the Physical World

6 citations · 16 across the 10 of their papers we have counts for

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cs.RO2026

Update-Free On-Policy Steering via Verifiers

Maria Attarian, Ian Vyse, Jasper Gerigk +7

In recent years, Behavior Cloning (BC) has become one of the most prevalent methods for learning manipulation from human demonstrations. Despite their successes, BC policies are of…

cs.RO20251 cited

Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer

Gemini Robotics Team, Abbas Abdolmaleki, Saminda Abeyruwan +169

General-purpose robots need a deep understanding of the physical world, advanced reasoning, and general and dexterous control. This report introduces the latest generation of the G…

cs.RO20256 cited

Gemini Robotics: Bringing AI into the Physical World

Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie +115

Recent advancements in large multimodal models have led to the emergence of remarkable generalist capabilities in digital domains, yet their translation to physical agents such as…

cs.RO2025

Predictive Red Teaming: Breaking Policies Without Breaking Robots

Anirudha Majumdar, Mohit Sharma, Dmitry Kalashnikov +3

Visuomotor policies trained via imitation learning are capable of performing challenging manipulation tasks, but are often extremely brittle to lighting, visual distractors, and ob…

cs.RO20242 cited

Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs

Hao-Tien Lewis Chiang, Zhuo Xu, Zipeng Fu +19

An elusive goal in navigation research is to build an intelligent agent that can understand multimodal instructions including natural language and image, and perform useful navigat…

cs.RO2024

Embodied AI with Two Arms: Zero-shot Learning, Safety and Modularity

Jake Varley, Sumeet Singh, Deepali Jain +5

We present an embodied AI system which receives open-ended natural language instructions from a human, and controls two arms to collaboratively accomplish potentially long-horizon…