Papers by Sungmin Jo

1 papers
ThinkBrake: Efficient Reasoning via Log-Probability Margin Guided Decoding (2026.findings-acl)

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Challenge: Recent advances in Large Reasoning Models (LRMs) have demonstrated remarkable capabilities across various tasks.
Approach: They propose a system that stops reasoning when the margin between continuation token and lt;/think gt; narrows.
Outcome: The proposed model reduces thinking token usage by 30% and improves accuracy by 8% while reducing thinking tokens by 72%.

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