Pith. sign in

Paper Citation Record · LEDGER

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

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 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 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:15:53.279616Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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.

source=pdf_text observed=2026-08-12T20:01:55.727730Z digest=sha256:e7e5ddc21fb7e68661ef26b34d4c060d0a041e21c3c2296d66b864acebe7f5ee

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.

source=pdf_text observed=2026-08-12T14:01:09.390704Z digest=sha256:72132636b95d4c82c2496a0409426a5be343afc26540e47368010cf94647a61c

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.

source=pdf_text observed=2026-08-08T17:06:03.034226Z digest=sha256:356425f655d3c1ca72e4ef5c4d357892d6f0aeb9137ddc770f9f6388a51c7a4c

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:27:19.768330Z digest=sha256:d9c21f3df220dda7e44cb9e565dc44ab0df14b323e395e4b784bbf45adf0d9cb

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.

source=pdf_text observed=2026-08-07T15:18:25.079473Z digest=sha256:e02efef2abdbcca9e74071bdda9f96cd4471446087ea37b8949cd76ca3abc47d

Observation de1fbf4a-d06e-49b6-b1c0-a2c6c2353ec0 · inbound

DELPHYNE: A Pre-Trained Model for General and Financial Time Series cites this paper.

DELPHYNE: A Pre-Trained Model for General and Financial Time Series Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:53.279616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:53.279616Z digest=sha256:e2a486f3f079b6f88beceb2ae88c28fb9f3fa7ca60ab23e82f52854c577cbf83

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.

source=pdf_text observed=2026-08-06T18:49:24.995738Z digest=sha256:8ba5e0fcab126f662ec37da11e08f2776178c6a09c2cdeca11c60808dbe838d9

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.

source=pdf_text observed=2026-08-06T23:26:36.600484Z digest=sha256:8f9af7988b3fa83bcd60fad3e210ae58407fb94dfd5048af5e6fab97b92ff039

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.

source=pdf_text observed=2026-08-06T15:04:11.116272Z digest=sha256:3e269d621c5027e6c5dcc65fb9da22fd48478e662c621ec2bba2b3b2379abff7

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T21:52:27.888915Z digest=sha256:6a95947191819aa17cd358b4a746b17a38eee55eec76b97937f40cdffa39b152

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-10T19:27:13.210860Z digest=sha256:f759addf1e76135f7dd4446b8d1d3bc05f4be0b0ed8974408831d89e321c2da4

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-12T02:10:12.434970Z digest=sha256:c7b9ff09f04adc340cea40d6e9a910d0a7a6e0e4d2129606ffef482a435e18a0

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T01:20:09.112090Z digest=sha256:90d980bf0f5e996d30fd4971f175aac8dd00a62ebe35faa4d5d7ac60d49c5218

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-27T10:19:31.255751Z digest=sha256:d103c0efc42cbfd5ba05b7e60a954477e02c7b916b74545360d37497d547775e

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-10T10:54:22.996938Z digest=sha256:d0cae6f07f31e0e6fc6fcf896538547ef13fb60985c30b5396a408d6bb67bdc6

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.

source=pdf_text observed=2026-08-02T09:17:11.938665Z digest=sha256:889bd66018e1fa2446bf8dfeb55a237c73cd668f97363922b65acfa5cacbf626

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.

source=pdf_text observed=2026-08-01T05:16:38.475451Z digest=sha256:0991ddbdbf3748cb1b75b18d9a39dab826acd86025209b48a9800f9ca83cfc48

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.

source=pdf_text observed=2026-08-04T22:11:25.081368Z digest=sha256:d6b850bb4804900141194216ef1c2c3cbe97332309f11ba2e4da8c5095b5d89c