Gemini Robotics ER 2: powering robotics with video understanding, task orchestration, and multi-robot collaboration
Gemini Robotics ER 2 helps robots reason, collaborate, and solve real-world tasks. It represents a step change in video understanding, tool orchestration, and multi-robot collaboration for robotic applications.
More from the blog
EmbeddingGemma 2: an open, lightweight multimodal embedding model
Computational tools for society’s most complex challenges
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Zotero Tutorialero
Zotero is a powerful open source reference manager that looks complicated at first, but is worth configuring properly once with plugins. This tutorial is aimed especially at researchers and doctoral students who want to use Zotero to manage literature and want a more efficient workflow. The post Zotero Tutorialero appeared first on GPT-Lab.
Related papers
Transformer-Based Autonomous Driving Models and Deployment-Oriented Compression: A Survey
This survey reviews representative Transformer-based autonomous driving models and organizes them by task role, sensing configuration, and architectural design and analyzes how efficiency constraints reshaping model design choices in practice affects deployability, robustness, and safety.
SurgRAW: Multi-Agent Workflow With Chain of Thought Reasoning for Robotic Surgical Video Analysis
This work introduces SurgCoTBench, the first reasoning-focused benchmark in RAS, and proposes SurgRAW, a clinically aligned Chain-of-Thought (CoT) driven agentic workflow for zero-shot multi-task reasoning in surgery, which surpasses mainstream VLMs and agentic systems and outperforms a supervised model.
AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots
This work proposes AtomicVLA, a unified planning-and-execution framework that jointly generates task-level plans, atomic skill abstractions, and fine-grained actions, and introduces a flexible routing encoder that automatically assigns dedicated atomic experts to new skills, enabling continual learning.
Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-Based Robots
This paper introduces POEF (POlicy EFfective Jailbreak), an automated red-teaming framework that takes into account the robot-specific constraints during both the optimization and evaluation processes and proposes two defense strategies that mitigate the behavior jailbreak risks.