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Paper Citation Record · LEDGER

Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2106.13008.

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

pith.paper-citation-record.v1
2106.13008 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T11:15:46.691621Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T10:57:05.504072Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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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 7468e32f-ac55-49f6-8f29-f7f057af91ec · inbound

Characteristic Root Analysis and Regularization for Linear Time Series Forecasting cites this paper.

Characteristic Root Analysis and Regularization for Linear Time Series Forecasting Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-18T12:51:23.453404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-18T12:49:02.077485Z digest=sha256:0f313f7d926222d457b401354629ab79dc2ce4d73780cd9bee1529e14f88cd44

Observation 4e862459-b2cb-4141-ad29-729314eae227 · inbound

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis cites this paper.

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-21T20:24:21.562327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-21T20:23:40.207908Z digest=sha256:f308ac22d3549a383db3d05f87ba3459bfe1e5887175c921315c6d08a767f137

Observation 02d6c649-85fc-4e5e-b2ae-0e68c6d7fb17 · inbound

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis cites this paper.

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T11:15:46.691621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:15:46.691621Z digest=sha256:3940f038612685ead9fec787c021ed7d970e50f98fa49c1ad9ee9658bb969461

Observation a7ccb8b3-b840-4fd0-87ac-01a9b2281298 · inbound

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-17T04:39:03.436426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-17T04:34:43.406156Z digest=sha256:3117843cd05bfc880f02be610a08612df4c1c52b8492442eaaa27f9ec0ea3e4b

Observation 7377e9a7-8d6e-4a03-97ba-0fed1e4c9e99 · inbound

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-21T18:20:29.088945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-21T18:18:33.265640Z digest=sha256:58b49526f99c0db73600cbca8c1e40f57d21c468698b49f3c2f95f088378180c

Observation b21bda75-4011-46d8-b93b-4e31d226f25e · inbound

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis cites this paper.

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T20:16:41.451376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:16:41.451376Z digest=sha256:28e548811aecde280235e2d8f62ca58b3b9e6a4805258f0eb0bdb7d0dfd8760c

Observation b136db17-f165-4324-98f9-5ae128a064fa · inbound

Neural CDEs as Correctors for Learned Time Series Models cites this paper.

Neural CDEs as Correctors for Learned Time Series Models Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-16T23:28:41.085695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T23:23:44.658505Z digest=sha256:44d866dfe87dc470d7361f12204db5905082201d685987b47baa363201ca35a2

Observation 4c940109-0389-4e69-ae07-1297dc9ca2c5 · inbound

MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations cites this paper.

MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T21:17:58.915764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-14T21:16:39.851664Z digest=sha256:7a184abecd5440ff33a457a3d5d58dd04234c24615123bb4383ae7eb66890239

Observation 5ed60f99-3538-472f-bea2-d0388d587b5b · inbound

Dynamic Linear Coregionalization for Realistic Synthetic Multivariate Time Series cites this paper.

Dynamic Linear Coregionalization for Realistic Synthetic Multivariate Time Series Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:30:52.352423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T19:03:55.571371Z digest=sha256:0415a2fae02a515046aaf691d7c2082dfe9d68432beb572ab9dfd5b6c096b9fc

Observation 6c38d9b0-96ef-4cd2-a2fb-c67795c2c409 · inbound

Dynamic Linear Coregionalization for Realistic Synthetic Multivariate Time Series cites this paper.

Dynamic Linear Coregionalization for Realistic Synthetic Multivariate Time Series Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:46:39.488422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T01:56:28.019565Z digest=sha256:0ee3455bc5bfcb5d8fb212a18e3750b0338c823419cf67a33156279400c54e34

Observation a2ad971b-eff8-45cb-b472-b9af841b8e3f · inbound

Signed Dual Attention: Capturing Signed Dependencies in Time Series Forecasting cites this paper.

Signed Dual Attention: Capturing Signed Dependencies in Time Series Forecasting Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-02T07:26:45.527560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T07:00:04.541121Z digest=sha256:ff764b3c1135785dd92a994f99d17c8016bad108f722610040c8f12e954a61e4

Observation 999f46e7-79ea-48ad-9453-40cd7b23a0aa · inbound

Exogenous Dropout: A Simple, Strong Baseline for Corruption-Robust Time Series Forecasting with Covariates cites this paper.

Exogenous Dropout: A Simple, Strong Baseline for Corruption-Robust Time Series Forecasting with Covariates Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-11T19:41:55.651993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T19:41:55.651993Z digest=sha256:1a0986340e2f9c16cf8287fef846b7ce068bbca0bc0f76cfa13588ab57b68f11

Observation 29550a86-7c29-4f48-9532-e4430c7a87fa · 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 Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Reference 16

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T10:57:05.505450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-10T10:54:22.996938Z digest=sha256:a196a99e6d3052db5c77499fa8cfa9bdc13e5967003004a053e8da02b208fee7