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This is really cool work on our synthetic hospital benchmark. For patient diagnosis, this shows that small models + SFT + the right tools > GPT-6 Luna. Interesting is that the tools help small models, but not big models. So gaps in capability can be replaced by tools
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"text": "spent a few days trying to train a tiny model to diagnose patients on the Synthetic Hospital environment out of CMU.\n\nRL didn't help much, but some SFT and a simple search tool got qwen3-4b to perform as well as a ~1T param model\n\nthis is because the agent is more than just the model.\n\n🧵:",
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