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Toto 2.0: Time Series Forecasting Enters the Scaling Era research paper by Datadog, 2026

Datadog · May 19, 2026 · Agents and evaluation · 12 citations · 39 upvotes · unverified

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What it shows

Time series foundation models demonstrate scalable forecasting performance across parameter sizes, with Toto 2.0 achieving state-of-the-art results on multiple benchmarks through a unified training approach.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Emaad Khwaja, Chris Lettieri, Gerald Woo and 10 more
arXiv
2605.20119 · PDF
Venue
arXiv.org
Citations
12, 6 influential · Semantic Scholar
Upvotes
39 · Hugging Face
Code
github.com/DataDog/toto
Lab
Datadog · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf

Changes

What changed
Influential citationsfirst count: 6Sep 25, 2026
Citationsfirst count: 12Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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