Model Detail
Cohere: Command R7B (12-2024)
—Commanding Humanoid by Free-form Language: A Large Language Action Model with Unified Motion Vocabulary
arXiv:2511.22963v2 Announce Type: replace-cross Abstract: Enabling humanoid robots to follow free-form language commands is critical for seamless human-robot interaction, collaborative task execution, and general-purpose embodied intelligence. While recent advances have improved low-level humanoid l
Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection
arXiv:2506.19420v2 Announce Type: replace Abstract: Multimodal sarcasm understanding is a high-order cognitive task. Although large language models (LLMs) have shown impressive performance on many downstream NLP tasks, growing evidence suggests that they struggle with sarcasm understanding. In this
Smart Commander: A Hierarchical Reinforcement Learning Framework for Fleet-Level PHM Decision Optimization
arXiv:2604.07171v1 Announce Type: new Abstract: Decision-making in military aviation Prognostics and Health Management (PHM) faces significant challenges due to the "curse of dimensionality" in large-scale fleet operations, combined with sparse feedback and stochastic mission profiles. To address th
Precise Robot Command Understanding Using Grammar-Constrained Large Language Models
arXiv:2604.04233v1 Announce Type: cross Abstract: Human-robot collaboration in industrial settings requires precise and reliable communication to enhance operational efficiency. While Large Language Models (LLMs) understand general language, they often lack the domain-specific rigidity needed for sa
Google Home’s latest update makes Gemini better at understanding your commands
Google is launching another update to its Home app, which is supposed to make controlling your smart home with its Gemini AI assistant "more natural and reliable," according to this week's release notes. With the update, you can describe the type of lighting you want, such as "the color of the ocean
Robust Global-Local Behavior Arbitration via Continuous Command Fusion Under LiDAR Errors
arXiv:2603.27273v1 Announce Type: cross Abstract: Modular autonomous driving systems must coordinate global progress objectives with local safety-driven reactions under imperfect sensing and strict real-time constraints. This paper presents a ROS2-native arbitration module that continuously fuses th
