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## Introduction
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X-Reasoner, a vision-language model posttrained solely on general-domain text for generalizable reasoning, using a twostage approach: an initial supervised fine-tuning phase with distilled long chainof-thoughts, followed by reinforcement learning with verifiable rewards. Experiments show that X-Reasoner successfully transfers reasoning capabilities to both multimodal and out-of-domain settings, outperforming existing state-of-theart models trained with in-domain and multimodal data across various general and medical benchmarks. More details can be found in the paper: https://arxiv.org/abs/2505.03981
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## Requirements
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We recommend installing the transformers version used in our experiments and other dependencies with this command:
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## Introduction
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We introduce X-Reasoner, a vision-language model posttrained solely on general-domain text for generalizable reasoning, using a twostage approach: an initial supervised fine-tuning phase with distilled long chainof-thoughts, followed by reinforcement learning with verifiable rewards. Experiments show that X-Reasoner successfully transfers reasoning capabilities to both multimodal and out-of-domain settings, outperforming existing state-of-theart models trained with in-domain and multimodal data across various general and medical benchmarks. More details can be found in the paper: [X-Reasoner: Towards Generalizable Reasoning Across Modalities and Domains](https://arxiv.org/abs/2505.03981)
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## Requirements
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We recommend installing the transformers version used in our experiments and other dependencies with this command:
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