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Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL
Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environments. Hand-curated environments with fixed task and reward difficulties become ineffective signals as model performance improves, and sparse rewards over long horizons induce mode collapse on s
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