Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.13338.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T12:09:14.531442Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T04:37:36.602264Z
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 b551bd54-cb91-4678-8bb9-6e623ada238e · inbound
IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning cites this paper.
IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
Reference 2013
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T12:09:14.531442Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 88884b48-be83-4d60-8fb1-20ee26ca446c · inbound
Cross-Domain Conditional Diffusion Models for Time Series Imputation cites this paper.
Cross-Domain Conditional Diffusion Models for Time Series Imputation SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:57:04.085464Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d61734e7-95f7-416b-acce-12ed176dde16 · inbound
Multivariate Time Series Data Imputation via Distributionally Robust Regularization cites this paper.
Multivariate Time Series Data Imputation via Distributionally Robust Regularization SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T08:42:36.953679Z
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.
Observation 1518f5e3-d745-4be6-aa0b-075b98f3a390 · inbound
UPLOTS: A Unified Pretrained Language Model for Constrained Time-series Generation cites this paper.
UPLOTS: A Unified Pretrained Language Model for Constrained Time-series Generation SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T04:37:36.603872Z
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.
Observation 37272ba9-9488-4283-a225-1c383144e3cc · inbound
Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework cites this paper.
Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
Reference 100
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T19:49:55.908962Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.