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Paper Citation Record · LEDGER

Ti-MAE: Self-Supervised Masked Time Series Autoencoders

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2301.08871.

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

pith.paper-citation-record.v1
2301.08871 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:42:52.170851Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T23:14:01.034889Z

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 6b18d97a-8337-403d-a7e0-41dc2b83f240 · inbound

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping cites this paper.

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-24T08:34:11.882001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T08:31:08.898349Z digest=sha256:19f623088236c17fa4a07fc1f9c0fbdaefaa382c14af9e6d73adccc0e85e01f6

Observation d587e92f-56ef-4a22-bf74-fbae5910c5db · inbound

Universal Time-Series Representation Learning: A Survey cites this paper.

Universal Time-Series Representation Learning: A Survey Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 117

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:28:53.413393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T04:26:45.527625Z digest=sha256:9ea45105d86729d5f9d3d220560300a78c4a2455cb362f992ad8e6a9df6e2af1

Observation d6a7c9e9-d073-4388-86e7-797b6e5db524 · inbound

TopoCL: Topological Contrastive Learning for Time Series cites this paper.

TopoCL: Topological Contrastive Learning for Time Series Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-09T10:42:52.170851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:42:52.170851Z digest=sha256:cebd4dda0dca8f02259d4d3c899e818faa17666bd4b447e0ec611f9f51534c1d

Observation 0c74f401-9aa6-4d81-aac7-44052b5ca2a4 · inbound

LSM-2: Learning from Incomplete Wearable Sensor Data cites this paper.

LSM-2: Learning from Incomplete Wearable Sensor Data Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T10:29:47.691657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:29:47.691657Z digest=sha256:8289435d5983d28af6ca9af9da9bcf08ff3e51458cbfe66e90fd9ee5fd2d9851

Observation fd5f9ec3-9c86-4ca4-9fa7-afe234c8c86b · inbound

Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates cites this paper.

Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T00:54:49.822354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:54:49.822354Z digest=sha256:2cfdd44b274b7d2e915489d8bd43b2daecd082b51c1773e18d037d254b1c552f

Observation 1edbbc1f-35cc-4ae7-9b10-dd305dba2cf4 · inbound

ST-MTM: Masked Time Series Modeling with Seasonal-Trend Decomposition for Time Series Forecasting cites this paper.

ST-MTM: Masked Time Series Modeling with Seasonal-Trend Decomposition for Time Series Forecasting Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T04:12:49.488556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:12:49.488556Z digest=sha256:d0d080e3bdedfc227f444b82c4ec1cde2e5689038918fd8a68aff3a9d02d9d45

Observation 4e1a0e42-380f-4902-8a04-3a77196cb8cb · inbound

Farm-Level, In-Season Crop Identification for India cites this paper.

Farm-Level, In-Season Crop Identification for India Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T21:33:09.011540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:33:09.011540Z digest=sha256:2889f80a4d72eac04eb37e02a6d824d10d8ed6bdfab5e10bb7d2633a91b6bfe8

Observation a9b06404-e90c-4ffd-9c34-22730446c8a8 · inbound

Masked Autoencoders for Ultrasound Signals: Robust Representation Learning for Downstream Applications cites this paper.

Masked Autoencoders for Ultrasound Signals: Robust Representation Learning for Downstream Applications Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T15:02:49.390950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:02:49.390950Z digest=sha256:b19124c57e2834fe6e917bb1c367c2d6fab40a69b7a42dff17622cf5c3c9588b

Observation 7f8f99cf-b842-4eb7-8844-4a7f6e856fca · inbound

Self-Distillation of Hidden Layers for Self-Supervised Representation Learning cites this paper.

Self-Distillation of Hidden Layers for Self-Supervised Representation Learning Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-02T18:11:34.065674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T18:11:34.065674Z digest=sha256:98df20f46b692ecfc0354e7b50718fce718c5381b2f2aae0f063e7b60226a8cd

Observation aedc75c8-eded-49ce-8226-c807e8bb4020 · inbound

Assessing the Potential of Masked Autoencoder Foundation Models in Predicting Downhole Metrics from Surface Drilling Data cites this paper.

Assessing the Potential of Masked Autoencoder Foundation Models in Predicting Downhole Metrics from Surface Drilling Data Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:40:19.041543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T11:38:53.305600Z digest=sha256:5c42c0294c1137b9270dd1c0b28c5fe0e4c693881d18aef2e7b51b936d7ab384

Observation bd14a77f-4307-46fe-9cec-d609b3f954fa · inbound

Do Masked Autoencoders Improve Downhole Prediction? An Empirical Study on Real Well Drilling Data cites this paper.

Do Masked Autoencoders Improve Downhole Prediction? An Empirical Study on Real Well Drilling Data Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:06:05.773304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T02:18:55.811833Z digest=sha256:9fad86fb44b148394d24754aec353f22569fb88d1a87777567e589267b2b28c6

Observation 04c31158-6fd8-4826-a1ed-5eded09db0eb · inbound

Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization cites this paper.

Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T15:21:08.483230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-09T20:11:49.088371Z digest=sha256:ea4215b6012ea228cf676fb2b9fe027e46d965c9c4f29d5abeb8a3f6333b7862

Observation bec98f8f-e405-4367-b529-89bc38b7b8b3 · inbound

Martingale-Consistent Self-Supervised Learning cites this paper.

Martingale-Consistent Self-Supervised Learning Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:57:28.095430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T06:54:04.297774Z digest=sha256:e6e6e7a8c2d3d77f3969dd87d9ce1ee54c52781a6b75820344af9994652c9632

Observation 1e0f9948-06fa-4dbf-b289-6db6d10ec196 · inbound

On the Role of Inductive Bias in Time-Series Pretraining: A Case Study in Learning Generalizable Representations for Clinical Time Series cites this paper.

On the Role of Inductive Bias in Time-Series Pretraining: A Case Study in Learning Generalizable Representations for Clinical Time Series Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:14:01.037147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T23:13:43.379357Z digest=sha256:60baf96b2849fdad38d6cb40c119c7f890ff308bce1275c00b6fe78dfa20a3c5