Pandora's AI Model Routing Box: Efficient Allocation with Costly Value Estimation

Key points

It formalized the model-routing problem of deciding when to call an expensive value estimator as the Pandora's box problem from economics.
Under a Gaussian-signal assumption, it computed the value of information and reservation prices in closed form to build a centralized Pandora router.
The Pandora router used far fewer expensive estimator calls while maintaining allocation quality similar to exhaustive evaluation.
It validated centralized and auction-based allocation in three domains: multiple language models, retrieval-augmented experts, and mathematical models with adjustable reasoning time.
The approach is limited to Gaussian assumptions and two-stage estimators, and in distributed auctions, strategic experts' gains can undermine overall efficiency when evaluations of other parties are inaccurate.

External research summaries. These are not HDATF publications or measured product results.