Lambda

Drift rate

Drift by model

Every endpoint lambda serves, on one timeline. Each strip is that endpoint's drift from its own reference period; dots mark detected changes, placed at the drift level they reached. Shared y-scale within each method, so strip heights are comparable.

LT change B3IT change line = drift from baseline · dot height = how far it moved hover or tap a strip to read every endpoint on the same day

Serving variants

a provider's quantizations are separate serving stacks and drift separately
VariantEndpointsLT drift rate MonitoringChangesB3IT

Endpoints

Ever changed Tracked
Endpoint Status Changes Methods Last change Drift from baseline

Timothée Chauvin, Erwan Le Merrer, François Taïani, Gilles Tredan (2026), "Log Probability Tracking of LLM APIs". ICLR 2026. https://arxiv.org/abs/2512.03816

Timothée Chauvin, Clément Lalanne, Erwan Le Merrer, Jean-Michel Loubes, François Taïani, Gilles Tredan (2026), "Token-Efficient Change Detection in LLM APIs". ICML 2026. https://arxiv.org/abs/2602.11083

@inproceedings{
chauvin2026log,
title={Log Probability Tracking of {LLM} {API}s},
author={Timothee Chauvin and Erwan Le Merrer and Francois Taiani and Gilles Tredan},
booktitle={The Fourteenth International Conference on Learning Representations},
year={2026},
url={https://openreview.net/forum?id=hFxivbAgVP}
}

@inproceedings{
chauvin2026tokenefficient,
title={Token-Efficient Change Detection in {LLM} {API}s},
author={Timothee Chauvin and Cl{\'e}ment Lalanne and Erwan Le Merrer and Jean-Michel Loubes and Francois Taiani and Gilles Tredan},
booktitle={Forty-third International Conference on Machine Learning},
year={2026},
url={https://openreview.net/forum?id=7cMlZZYZT0}
}