UniRL-Zero: Reinforcement Learning on Unified Models with Joint Language Model and Diffusion Model Experts
Abstract
UniRL-Zero is a unified reinforcement learning framework that enhances multimodal language model understanding, diffusion model generation, and their interactive capabilities through defined scenarios and systematic baselines.
We present UniRL-Zero, a unified reinforcement learning (RL) framework that boosts, multimodal language model understanding and reasoning, diffusion model multimedia generation, and their beneficial interaction capabilities within a unified model. Our work defines six scenarios for unified model reinforcement learning, providing systematic baselines for reinforcement learning of unified understanding and generation model. Our code is available at https://github.com/G-U-N/UniRL.
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