Research on small reasoning models (sRMs) finds that scaling test-time computation is not always the right operation, based on interventions at intermediate reasoning states across two model families. The work examines when additional thinking fails to help small reasoning models reason beyond their parametric knowledge.
Scaling test-time computation is a powerful way to improve language-model reasoning, and is particularly appealing for small reasoning models (sRMs) that are cheap to serve. However, is additional thinking always the right operation? By intervening at intermediate reasoning states across two model f
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