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Scaling Automatic Research Agents via World Models

452 upvotes · 29 AUG 2026 · Xiyuan Yang, Sheikh Sarwar, Jingru Cheng et al.

This paper proposes a method to scale automatic research agents by replacing environment execution with a world model, which can reduce training costs and improve performance. Practitioners might care about this approach because it can accelerate training times and lead to better results for complex AI tasks.

continual learningautomatic research agentsworld modelsreinforcement learningbenchmarks