Paper Citation Record · LEDGER

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2401.03955.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2401.03955 v8

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:01:55.727730Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-10T10:57:05.483805Z

Reference resolution

0 of 0 outbound references displayed

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verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c2debc25-8a41-43df-b315-53f1d4eae855 · inbound

Causal Time-Series Synchronization for Multi-Dimensional Forecasting cites this paper.

Causal Time-Series Synchronization for Multi-Dimensional Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T20:01:55.727730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1642a23c-2dc9-4621-8fcb-339b3c378bcb · inbound

Beyond Data Scarcity: A Frequency-Driven Framework for Zero-Shot Forecasting cites this paper.

Beyond Data Scarcity: A Frequency-Driven Framework for Zero-Shot Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-12T14:01:09.390704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adf20b76-d87f-4185-b7cc-717fe7f2df69 · inbound

Investigating Compositional Reasoning in Time Series Foundation Models cites this paper.

Investigating Compositional Reasoning in Time Series Foundation Models Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T17:06:03.034226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa1d415c-78c9-4baf-80c3-3f138197388f · inbound

MoTime: A Dataset Suite for Multimodal Time Series Forecasting cites this paper.

MoTime: A Dataset Suite for Multimodal Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:19.768330Z

Source-reported events for the cited work

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Observation 65de7bb9-8ac2-4e23-bccd-eeaf00db5e8b · inbound

EPBench: A Benchmark for Short-term Earthquake Prediction with Neural Networks cites this paper.

EPBench: A Benchmark for Short-term Earthquake Prediction with Neural Networks Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:18:25.079473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 076fdc1c-b5cb-4ec8-bf94-1468b3e78897 · inbound

Time Series Foundation Models for Multivariate Financial Time Series Forecasting cites this paper.

Time Series Foundation Models for Multivariate Financial Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:24.995738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e0dd085-3cd6-4ccb-885c-5273d5faf845 · inbound

A Survey of AIOps in the Era of Large Language Models cites this paper.

A Survey of AIOps in the Era of Large Language Models Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T23:26:36.600484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0ea8d4c-7972-4f6e-ad70-57b960f38977 · inbound

Causal Graph Fuzzy LLMs: A First Introduction and Applications in Time Series Forecasting cites this paper.

Causal Graph Fuzzy LLMs: A First Introduction and Applications in Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T15:04:11.116272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0747e8a2-1b26-4730-b63b-00a853e579de · inbound

Triplet Feature Fusion for Equipment Anomaly Prediction : An Open-Source Methodology Using Small Foundation Models cites this paper.

Triplet Feature Fusion for Equipment Anomaly Prediction : An Open-Source Methodology Using Small Foundation Models Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-15T21:56:40.997799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 32bdf94e-a63b-451f-bfab-b26d7b3c38b6 · inbound

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting cites this paper.

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:55:52.199693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1e7ee60b-bb4d-4c74-b69c-f57923fa7a0a · inbound

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting cites this paper.

MICA: Multivariate Infini Compressive Attention for Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:11:15.606723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e3952866-9c5a-4727-b4f1-692bf75c2ac5 · inbound

Adaptive Conformal Anomaly Detection with Time Series Foundation Models for Signal Monitoring cites this paper.

Adaptive Conformal Anomaly Detection with Time Series Foundation Models for Signal Monitoring Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T13:36:09.853869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9a20d08f-9c18-42e5-a582-7c740c04eac4 · inbound

TimeRouter: Efficient and Adaptive Routing of Time-Series Foundation Models cites this paper.

TimeRouter: Efficient and Adaptive Routing of Time-Series Foundation Models Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:47:59.798961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1bebcde8-cf4c-4d51-b916-7b0c3e4f0f5e · inbound

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting cites this paper.

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:57:05.485274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation aefb5d5a-d815-40f1-8924-9931341a7f70 · inbound

Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule cites this paper.

Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T09:17:11.938665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98f4ae6f-f64b-469a-8d5a-dc55daad3f74 · inbound

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting cites this paper.

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T05:16:38.475451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d922063-f713-49d4-8e56-d26777aba395 · inbound

CENTILE: A Telemetry Foundation Model Evaluated by the Decisions It Drives cites this paper.

CENTILE: A Telemetry Foundation Model Evaluated by the Decisions It Drives Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T22:11:25.081368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.