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Tabby: Open-Source Time Series Foundation Model Unveiled

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced Tabby, an open-source probabilistic time series foundation model designed for long contexts. Tabby utilizes an encoder-only patch Transformer architecture and was trained on a diverse corpus of real-world and synthetic data. The model supports various downstream tasks including forecasting, classification, and anomaly detection, achieving competitive zero-shot performance on several benchmarks. This development aligns with a broader trend of creating foundation models beyond large language models, extending their capabilities to structured data like time series. AI

IMPACT This release contributes to the growing field of foundation models for structured data, potentially accelerating ML system development beyond language tasks.

RANK_REASON The cluster describes the release of a new research paper detailing an open-source model for time series analysis.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Tabby: Open-Source Time Series Foundation Model Unveiled

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The cluster describes the release of a new research paper detailing an open-source model for time series analysis.
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model release, paper, product
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58 days old
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Shifeng Xie, Bahaeddine Abdessalem, Zehao Xiao, Youssef Attia El Hili, Ambroise Odonnat, Zhiwei Dong, Lei Zan, Themis Palpanas, Jianfeng Zhang, Lujia Pan, Keli Zhang, Malik Tiomoko ·

    Tabby: An Open Pretraining Recipe for Time Series Foundation Models

    arXiv:2609.13956v1 Announce Type: new Abstract: In this report, we release Tabby, a long context probabilistic time series foundation model, together with a complete and open recipe of how it was built. Tabby adopts an encoder-only patch Transformer architecture and concentrates …

  2. Towards AI TIER_1 English(EN) · Deepanshu Gupta ·

    Beyond LLMs: The Rise of Foundation Models for Tables, Time Series, and Structured Data

    <h4>Foundation models are now being developed for tables, time series, and other structured data. The important question is not what we call them, but whether they can make machine-learning systems faster and easier to build.</h4><figure><img alt="" src="https://cdn-images-1.medi…

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