Viktoriya Zhukova — accepted AI-conference papers

2026

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks

Zhongzheng Qiao, SHENG PAN, Anni Wang, Viktoriya Zhukova, Yong Liu, Xudong Jiang +4

ICML 2026poster

Time series foundation models (TSFMs) are revolutionizing the forecasting landscape from specific dataset modeling to generalizable task evaluation. However, we contend that existing benchmarks exhibit common limitations in four dimensions: constrained data composition dominated by reused legacy sou…

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2025

This Time is Different: An Observability Perspective on Time Series Foundation Models

Ben Cohen, Emaad Khwaja, Youssef Doubli, Salahidine Lemaachi, Chris Lettieri, Charles Masson +13

NeurIPS 2025poster

We introduce Toto, a time series forecasting foundation model with 151 million parameters. Toto uses a modern decoder-only architecture coupled with architectural innovations designed to account for specific challenges found in multivariate observability time series data. Toto's pre-training corpus…

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