arXiv AI October 31, 2026 By Chen Zhang, Kepu Zhang, Jiatong Zhang, Xiao Zhang, Jun Xu

Sandwich Reasoning: An Answer-Reasoning-Answer Approach for Low-Latency Query Correction

Sandwich Reasoning (SandwichR) introduces an Answer-Reasoning-Answer framework for low‑latency query correction, producing an initial correction, a reasoning step, and a refined final correction. It uses consistency‑aware reinforcement learning to align the initial and final answers and margin‑based rejection sampling to focus on samples where reasoning yields the most benefit. Experiments show SandwichR matches chain‑of‑thought accuracy while cutting latency by 40‑70%, addressing the latency‑accuracy trade‑off in real‑time search.

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