DUET: Efficient AI Inference via Collaborative Reasoning
A new framework called DUET (Dual-model Efficient Two-stage inference) enables efficient AI inference by splitting reasoning between a capable model and a lightweight model. The capable model generates a reasoning signal, which the lightweight model interprets to produce the final answer. A length-penalized joint training objective ensures the capable model transmits only sufficient information. This approach reduces inference costs without sacrificing task performance.
Key facts
- DUET stands for Dual-model Efficient Two-stage inference.
- It uses a capable model and a lightweight model working together.
- Inference is decomposed into two stages: reasoning signal generation and answer production.
- A length-penalized joint training objective encourages minimal information transmission.
- The framework maintains strong reasoning performance while reducing costs.
- The paper is from arXiv:2605.01111v1.
- The announcement type is cross.
- The approach avoids relying on a single large model for end-to-end reasoning.
Entities
Institutions
- arXiv