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# LogicCoder-8B
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**LogicCoder-8B** is
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This model was fine-tuned on pruned CoTs examples derived via our **ASAP** method(**A**nchor-guided, **S**urpris**a**l-polished **P**runing), focusing on highly compressed yet semantically informative reasoning traces.
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# Paper Page
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[**Pruning the Unsurprising: Efficient Code Reasoning via First-Token Surprisal.**](https://arxiv.org/abs/2508.05988)
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# LogicCoder-8B
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**LogicCoder-8B** is an 8B-parameter language model fine-tuned for code generation tasks. It is based on the DeepSeek-R1-Distill-Llama-8B model and trained on a Python subset of the open-r1/codeforces-cots dataset.
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This model was fine-tuned on pruned CoTs examples derived via our **ASAP** method(**A**nchor-guided, **S**urpris**a**l-polished **P**runing), focusing on highly compressed yet semantically informative reasoning traces.
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