Paper Citation Record · LEDGER

TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.05711.

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

pith.paper-citation-record.v1
2410.05711 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:51:10.560497Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6b07d9fc-16ca-46fe-916c-9479271120ef · inbound

Multimodal Conditioned Diffusive Time Series Forecasting cites this paper.

Multimodal Conditioned Diffusive Time Series Forecasting TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-16T05:51:10.560497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03f1c0f9-2bab-42ab-af43-c93c7003b07a · inbound

CoGenCast: A Coupled Autoregressive-Flow Generative Framework for Time Series Forecasting cites this paper.

CoGenCast: A Coupled Autoregressive-Flow Generative Framework for Time Series Forecasting TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T05:00:55.940463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b819a5aa-c2e7-48f3-a2ae-c3ce801e1304 · inbound

Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach cites this paper.

Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T05:30:56.649369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 22b54967-e500-4686-9346-31ee09763563 · inbound

Quantifying the Pre-training Dividend: Generative versus Latent Self-Supervised Learning for Time Series Foundation Models cites this paper.

Quantifying the Pre-training Dividend: Generative versus Latent Self-Supervised Learning for Time Series Foundation Models TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:13:06.535749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f16e8890-0904-4e77-86fe-ee3c10e19b0d · inbound

VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting cites this paper.

VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:36:17.589389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 38ff0569-1c02-4de2-9a51-8d032b4ce8e2 · inbound

Domain-Informed Multi-View Self-Distillation for Astronomical Light-Curve Representation Learning with JEPA cites this paper.

Domain-Informed Multi-View Self-Distillation for Astronomical Light-Curve Representation Learning with JEPA TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T01:34:09.325333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.