Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Using Pre-trained LLMs for Multivariate Time Series Forecasting
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.06386.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T18:32:33.268395Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T02:37:10.318927Z
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 e13be00d-8253-48cf-8a0e-e11cf6f9a3b5 · inbound
Multivariate Wireless Link Quality Prediction Based on Pre-trained Large Language Models cites this paper.
Multivariate Wireless Link Quality Prediction Based on Pre-trained Large Language Models Using Pre-trained LLMs for Multivariate Time Series Forecasting
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T18:32:33.268395Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3d6ac34e-a206-4da4-97af-5e77e9e7478f · inbound
Large Language models for Time Series Analysis: Techniques, Applications, and Challenges cites this paper.
Large Language models for Time Series Analysis: Techniques, Applications, and Challenges Using Pre-trained LLMs for Multivariate Time Series Forecasting
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:54.106385Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea300936-974c-46c8-b457-ded3f6a324b0 · inbound
Forecasting Commencing Enrolments Under Data Sparsity: A Zero-Shot Time Series Foundation Models Framework for Higher Education Planning cites this paper.
Forecasting Commencing Enrolments Under Data Sparsity: A Zero-Shot Time Series Foundation Models Framework for Higher Education Planning Using Pre-trained LLMs for Multivariate Time Series Forecasting
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T02:37:10.322931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.