TL;DR of the paper, generated automatically.

Paper claims a retrained draft model makes long agent tasks more accurate.

• Method: draft trained to reject critical reasoning tokens, so the target checks them.
• Claimed gain: higher end-to-end success on agentic coding benchmarks, target model unchanged.
• Training size: 0.06% to 0.28% of hosted parameters, per the authors.