unbiased

2 models, with 0 monitored endpoints (0 actively tracked, 0 no longer) across 0 providers. 0 of them show at least one detected change — the model version is nominally fixed, so the movement is in how it is served.

2
Models
0
Monitored endpoints
0
Actively tracked
0
Changes total
0
Providers

Models

Model Monitored endpoints Providers Changes Endpoints changed Last change
pareto-26.10 too expensive
1 too expensive
 0 0 — 0/0 —
pareto-26.9 too expensive
1 too expensive
 0 0 — 0/0 —
2 models

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}
}