A learned continue-thinking token, trained via RL on its embedding alone, improves math benchmark accuracy more than fixed-token budget forcing in a frozen language model.
In Advances in Neural Information Processing Systems
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Learning a Continue-Thinking Token for Enhanced Test-Time Scaling
A learned continue-thinking token, trained via RL on its embedding alone, improves math benchmark accuracy more than fixed-token budget forcing in a frozen language model.