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This Time is Different: An Observability Perspective on Time Series Foundation Models research paper by Datadog, 2025

Datadog · Agents and evaluation · May 20, 2025 · 79 citations · 40 upvotes · unverified

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What it shows

Toto is a time series forecasting foundation model using a decoder-only architecture, demonstrating state-of-the-art performance on large-scale benchmarks with multivariate observability data.

By Ben Cohen, Emaad Khwaja, Youssef Doubli and 14 more · arXiv 2505.14766 · PDF

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

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Agents and evaluationUnverifiedMay 19, 2026Toto 2.0: Time Series Forecasting Enters the Scaling EraTime 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.Datadog39 citations39 upvotesRead →ArchitecturesUnverifiedJul 10, 2024Toto: Time Series Optimized Transformer for ObservabilityToto, a Time Series Optimized Transformer for Observability, achieves state-of-the-art performance in observability and general-purpose forecasting using a vast dataset of time series data.Datadog47 citations33 upvotesRead →

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About this paper
Venue
Neural Information Processing Systems
Citations
79, 14 influential · Semantic Scholar
Upvotes
40 · Hugging Face
Lab
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Changes

CitationsNov 2, 2026Influential citations rose from 13 to 14.
CitationsNov 2, 2026Citations rose from 70 to 79.
CitationsOct 12, 2026Influential citations rose from 12 to 13.
CitationsOct 12, 2026Citations rose from 63 to 70.
CitationsOct 5, 2026Influential citations rose from 11 to 12.
CitationsOct 5, 2026Citations rose from 56 to 63.
CitationsSep 28, 2026Citations rose from 55 to 56.
CitationsSep 25, 2026A first count of 11 influential citations.
CitationsSep 25, 2026A first count of 55 citations.
New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.