World‑model RL accelerates LLM training by 3‑4
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Replacing the environment with a learned world model shrinks wall‑clock training time for LLM agents by several times (approximately 3–4×) while leaving benchmark scores intact. The field has long assumed that high‑fidelity sandbox execution is unavoidable once an agent leaves the generation phase,…
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- 2026-09-18 05:00 · DEV Community — Machine Learning
World‑model RL accelerates LLM training by 3‑4