Agents & InferencearXiv
Localized posterior inference cuts ocean turbulence calibration errors vs global methods
Which summary reads better? Pick one — models revealed after.Both summaries are AI-generated.
Summary A
Localized posterior inference reduces aggregate predictive errors by allowing model calibration parameters to adapt to different contexts, which is crucial for production LLM and agent deployments where context uncertainty is high, enabling more accurate predictions under varying conditions.
Summary B
Mistral Large quota or rate limit — check usage and plan. Original headline: Amortized Localized Posterior Inference for Model Calibration with Application to an Ocean Turbulence Closure
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