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# 🚀 Can we cast reward modeling as a reasoning task?
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**RM-R1** is a training framework for *Reasoning Reward Model* (ReasRM) that judges two candidate answers by first **thinking out loud**—generating structured rubrics or reasoning traces—then emitting its preference. Compared to traditional scalar or generative reward models, RM-R1 delivers **state-of-the-art performance** on public RM benchmarks while offering fully interpretable justifications.
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## 🧠 TL;DR
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# 🚀 Can we cast reward modeling as a reasoning task?
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**RM-R1** is a training framework for *Reasoning Reward Model* (ReasRM) that judges two candidate answers by first **thinking out loud**—generating structured rubrics or reasoning traces—then emitting its preference. Compared to traditional scalar or generative reward models, RM-R1 delivers **state-of-the-art performance** on public RM benchmarks on average while offering fully interpretable justifications.
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## 🧠 TL;DR
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