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Forget short-horizon RL: Odysseus proves VLMs can master 100+ turn decision-making in complex games, outperforming state-of-the-art models by 3x.
Domain-specific fine-tuning can induce "agentic collapse" in LLMs, but a surprisingly small amount of agentic data from *another* domain can bring those general tool-use skills roaring back.
Automating RL environment engineering slashes costs and unlocks massive speedups (up to 22,320x!) using a recipe of prompt engineering, verification, and agent-assisted repair.
