Paper Citation Record · LEDGER

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models

As of 23 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2412.06368.

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

pith.paper-citation-record.v1
2412.06368 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:51:08.520993Z

measured 24 of 24 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact1
verified fuzzy5
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 55a78540-e7d3-48a1-a0e8-11d98b97a100 · outbound

This paper cites GPT-4 Technical Report.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.424622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf770504-99b1-40d5-a19c-039ec3c9d8d9 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models On the Opportunities and Risks of Foundation Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.429940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba730bb1-9547-437f-a65d-a709df4f18de · outbound

This paper cites A., Bagnall, A., Kamgar, K., Yeh, C.-C.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models A., Bagnall, A., Kamgar, K., Yeh, C.-C

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:51:08.938517Z

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.

Observation a7594c7c-82a1-483b-ba02-dc621c041956 · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:51:08.927302Z

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.

Observation 09741066-0de8-42fa-871b-bb2443b5adaf · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.441348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9de3b21c-ecc5-4990-b1f0-b26b46d582d8 · outbound

This paper cites K., Li, X., and Guan, C.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models K., Li, X., and Guan, C

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:51:08.915819Z

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.

Observation 22af5c8a-afbd-4d25-a5ab-f053308ea6fe · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.449053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9f02bf8-d20d-4fce-9186-ca4018e1e624 · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.452796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 194d5c9a-35c9-4782-8b1b-a1eef6fb0e1c · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:51:08.895272Z

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.

Observation caabb1fb-a38e-43b4-81f8-5b134c205b06 · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.460565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fab04b5b-479d-4b5c-a83f-9ffe78641be2 · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:51:08.882813Z

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.

Observation ff01791b-3732-4191-9627-3e35a0fd2916 · outbound

This paper cites and Hutter, F.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models and Hutter, F

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:51:08.870386Z

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.

Observation 8230c427-806f-4f4c-8911-617af9d5cb8f · outbound

This paper cites Nguyen, N., Sinthong, P., and Kalagnanam, J.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Nguyen, N., Sinthong, P., and Kalagnanam, J

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:51:08.856247Z

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.

Observation bd862b25-424e-4931-bc33-b30431c9b54d · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Representation Learning with Contrastive Predictive Coding

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.477768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0fccc64-3697-4aa2-b91a-834d75fcd399 · outbound

This paper cites Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.486279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66a62db3-f2e6-4d6c-9183-29fb0a973669 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models LLaMA: Open and Efficient Foundation Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.490211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5fa4559-8d9c-414f-b4ba-396dade4ea7c · outbound

This paper cites and Isola, P.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models and Isola, P

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:51:08.844217Z

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.

Observation 39710760-b736-48b4-aa9f-56b4b2071ede · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:51:08.829974Z

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.

Observation 96b55d39-c8e9-4eee-a7a7-0290c3d5827a · outbound

This paper cites MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:51:08.572708Z

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.

Observation 42d5e568-a7a4-434d-977d-913cbec0ce0a · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:51:08.818106Z

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.

Observation 96fe088e-1115-4d28-93dd-125b9deb9750 · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:51:08.806024Z

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.

Observation 59cd791d-49ec-4f42-9f42-dafaf8204ef6 · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:51:08.690372Z

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.

Observation 48bb2127-6692-4a52-b10f-550836c2d4e8 · outbound

This paper cites an unresolved cited work.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:51:08.679143Z

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.

Observation 8e12f98d-56ec-423f-927f-f4930e9f9a48 · outbound

This paper cites One Fits All:Power General Time Series Analysis by Pretrained LM.

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models One Fits All:Power General Time Series Analysis by Pretrained LM

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T19:51:08.520993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.