Papers with Chain-of-Thought paradigm

1 papers
Think Smart, Not Hard: Difficulty Adaptive Reasoning for Large Audio Language Models (2026.findings-acl)

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Challenge: Existing methods to determine whether to perform reasoning lack fine-grained mechanisms to adapt reasoning length to problem complexity.
Approach: They propose a difficulty-adaptive reasoning method that dynamically links reasoning length to the model’s perceived problem difficulty.
Outcome: The proposed method reduces average reasoning length by 50%, achieving higher efficiency without sacrificing accuracy.

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