Context-Adaptive Inference: A Unified Statistical and Foundation-Model View
Modern predictive systems are expected to adapt their behavior to the specific situation they are facing. A clinical model should not treat every patient the same; a retrieval-augmented model should change its answer when given different evidence; a mixture-of-experts model should route different inputs to different experts. We call this capability context-adaptive inference: before predicting, the system uses information about the current context to specialize its parameters or computation for that instance. This article provides a unified view of context-adaptive inference across three traditions that are usually treated separately: (i) explicit adaptation in statistics (e.g. varying-co...
| Authors | Yue Yao, Caleb N. Ellington, Jingyun Jia et al. |
|---|---|
| Primary category | stat.ML |
| Published | 25 July 2026 |
| Last updated at source | 25 July 2026 |
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