MARS introduces a four-agent MLLM system for risk-aware planning and personalized assistance in home robotics, claiming superior performance over state-of-the-art multimodal models on multiple datasets.
arXiv preprint arXiv:2502.14917
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The paper provides the first comprehensive survey of multimodal chain-of-thought reasoning, including foundational concepts, a taxonomy of methodologies, application analyses, challenges, and future directions.
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MARS: Multi-Agent Robotic System with Multimodal Large Language Models for Assistive Intelligence
MARS introduces a four-agent MLLM system for risk-aware planning and personalized assistance in home robotics, claiming superior performance over state-of-the-art multimodal models on multiple datasets.
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Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey
The paper provides the first comprehensive survey of multimodal chain-of-thought reasoning, including foundational concepts, a taxonomy of methodologies, application analyses, challenges, and future directions.