Pith. sign in

Paper Citation Record · LEDGER

Ti-MAE: Self-Supervised Masked Time Series Autoencoders

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 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 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:29:47.691657Z

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

  • 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 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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-24T08:31:08.898349Z digest=sha256:7cbf5201b72246a94c1225a16d3b8f31d2ef25ee78f763cd083c25b090d10ec5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-24T04:26:45.527625Z digest=sha256:94ef101ec1bffcc79a310ac0e03d3c83abdfdeeb5f92cd6c11a4a943881dd666

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=sha256:024f6107588d851e521ad537e087391ca1a89e4c5a943fb154924d23ccbb8fab

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=sha256:679b782909667729454a93cb5a4829fa6a2d57ce7b26033e5af02ec07fbf04b1

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=sha256:9db44480f76783024617386f31c0f63779223aeaf00a51e5abaa4638bbd950e9

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=sha256:0ee3ab13e43204e050319b16b112b5814eea0a327682c3e1404913251a2e626c

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=sha256:828750b86f6086af6df2ba5f1e19e37fa1f2a4bcf4be808e23178bf4035c5fac

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=sha256:8ba9d54aebb7845f37aed2f4252a415dc7cbdc71cc1e8edb4851f7dfcb74dee7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T11:38:53.305600Z digest=sha256:80b6ef2572968ed345deb230d99ddae91cb6f17269a78a40d1f98082be832f72

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T02:18:55.811833Z digest=sha256:fc28540b26410caf7df8d7a95e9b53c303dcc41bd0188c5eb2c1d97a80761a24

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-09T20:11:49.088371Z digest=sha256:fcc036536694b6c12c56b5043a099b8b9064613645585c86689ab7e965c027fa

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T06:54:04.297774Z digest=sha256:d520c4333caba4a19c0416f98f433ce727c8e9bd4b972fc7e12887de0df2598b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T23:13:43.379357Z digest=sha256:64ed17f4e0f91ac41757202be0c90537f3d4ebc9a37ae1ee522b4aeb06057a4c