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  ---
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- license: mit
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  language:
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  - en
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  base_model:
@@ -35,7 +35,7 @@ Leverage OPC to tackle pressing research questions in automated proof generation
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  (2) How often do models that produce correct final answers truly reason their way to valid proofs?
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  (3) By what margin do best-of-n selection methods improveme proof quality?
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- WBuilding on this breakthrough resource, we present **OPC-R1-8B** - an open-source model for proof correctness judging that matches state-of-the-art performance. OPC-R1-8B ouperforms the majority of leading closed-source models, reaching an impressive 88.1% accuracy on verifying LLM-generated proofs.
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  ## Introduction
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  ---
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+ license: apache-2.0
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  language:
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  - en
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  base_model:
 
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  (2) How often do models that produce correct final answers truly reason their way to valid proofs?
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  (3) By what margin do best-of-n selection methods improveme proof quality?
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+ Building on this breakthrough resource, we present **OPC-R1-8B** - an open-source model for proof correctness judging that matches state-of-the-art performance. OPC-R1-8B ouperforms the majority of leading closed-source models, reaching an impressive 88.1% accuracy on verifying LLM-generated proofs.
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  ## Introduction
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