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  "text": "LLMs can't see.\n\nHow can we build effective multi-agent systems with vision capabilities?\n\nBuilding multimodal models from scratch is expensive. Training joint vision-language architectures requires massive compute, specialized datasets, and careful optimization.\n\nBut there's another way.\n\nThis new research introduces \"Be My Eyes,\" a framework where vision models become literal eyes for LLMs.\n\nThe key idea: multi-agent collaboration through natural language.\n\nVision agents analyze images and describe what they see. Language agents receive these descriptions and reason about them. Communication happens entirely through text.\n\nNo joint training. No architectural modifications. Just agents talking to each other.\n\nThe system is modular. Swap in better vision models as they emerge. Upgrade the LLM independently. Each component improves without retraining the whole system.\n\nResults on MMMU, MMMU-Pro, and video understanding benchmarks show competitive performance with specialized multimodal models.\n\nWhat makes this powerful: it challenges the assumption that multimodal AI requires unified architectures. Agent collaboration through language provides an efficient alternative.\n\nPaper: https://t.co/VqnwooAGkJ\nLearn to build with AI Agents in our academy: https://t.co/Y5kVy5iKiQ",
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