Paper Citation Record · LEDGER

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles

As of 18 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 1 inbound Pith citation observation for arXiv:2508.16641.

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

pith.paper-citation-record.v1
2508.16641 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:27:46.334470Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T13:03:25.032299Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T13:06:23.987913Z

Reference resolution

11 of 11 outbound references displayed

verified exact0
verified fuzzy4
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7668aa85-ddb5-472b-bf0b-49f82ac9196d · outbound

This paper cites Chronos: Learning the Language of Time Series.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles Chronos: Learning the Language of Time Series

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:46.276336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd64cb45-537c-4ecd-9019-e107e51daac5 · outbound

This paper cites UniTS: A Unified Multi-Task Time Series Model.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles UniTS: A Unified Multi-Task Time Series Model

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:46.282793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e578e2c-0b11-40f6-99a7-fc7a273e2436 · outbound

This paper cites TimeGPT-1.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles TimeGPT-1

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:46.288869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b386871-4f6e-4c29-a439-60875c547af8 · outbound

This paper cites MOMENT: A Family of Open Time-series Foundation Models.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles MOMENT: A Family of Open Time-series Foundation Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:46.295642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a6342a0-2677-4632-8b2a-8e87ed858a39 · outbound

This paper cites Empowering Time Series Analysis with Large Language Models: A Survey.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles Empowering Time Series Analysis with Large Language Models: A Survey

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:46.301773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b20754e5-55d6-49a2-96d6-cba157c2c2af · outbound

This paper cites Foundation models for time series analysis: A tutorial and survey.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles Foundation models for time series analysis: A tutorial and survey

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:27:46.550836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 45f679e0-cfcf-4f01-88f9-64bcb57f1623 · outbound

This paper cites Foundation models for time series.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles Foundation models for time series

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:27:46.533040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e4c7d1e3-1d45-4ccb-9f87-21198af5fb84 · outbound

This paper cites Introduction to time series analysis and forecasting.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles Introduction to time series analysis and forecasting

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:46.318836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db30ae4a-f120-48fe-9c9d-191a3bab505d · outbound

This paper cites Lag-llama: Towards foundation models for time series forecasting.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles Lag-llama: Towards foundation models for time series forecasting

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:27:46.502510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1e761a50-4557-408c-91d0-a6da95a21cd2 · outbound

This paper cites Autogluon--timeseries: Automl for probabilistic time series forecasting.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles Autogluon--timeseries: Automl for probabilistic time series forecasting

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:27:46.484607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e20fc6dd-4a31-4321-a133-8c753adf97d7 · outbound

This paper cites Unified Training of Universal Time Series Forecasting Transformers.

Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles Unified Training of Universal Time Series Forecasting Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T17:27:46.334470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d9ff36a2-504a-460b-8237-a8c0aa92f542 · inbound

ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters cites this paper.

ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters Enhancing Transformer-Based Foundation Models for Time Series Forecasting via Bagging, Boosting and Statistical Ensembles

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:06:23.990993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.