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Paper Citation Record · LEDGER

MSHyper: Multi-Scale Hypergraph Transformer for Long-Range Time Series Forecasting

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.09261.

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

pith.paper-citation-record.v1
2401.09261 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:50:11.691622Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T07:26:59.323054Z

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 4109cf08-3496-4953-92a1-0a1d29251d1a · inbound

ST-Hyper: Learning High-Order Dependencies Across Multiple Spatial-Temporal Scales for Multivariate Time Series Forecasting cites this paper.

ST-Hyper: Learning High-Order Dependencies Across Multiple Spatial-Temporal Scales for Multivariate Time Series Forecasting MSHyper: Multi-Scale Hypergraph Transformer for Long-Range Time Series Forecasting

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T11:50:11.691622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:50:11.691622Z digest=sha256:6d9cf08c57da29e101cb28495512359ad57b0095c4720af6299e26c43d2dc54e

Observation f026170e-14d6-4d31-90bd-913c079a1dc4 · inbound

MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting cites this paper.

MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting MSHyper: Multi-Scale Hypergraph Transformer for Long-Range Time Series Forecasting

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T10:42:46.158655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:42:46.158655Z digest=sha256:be788878034e04cc55b487b9ff85ab982caaba322679eccbf59c32d8a40c388e

Observation 07c3fe75-3b9f-4a32-a2e1-f995b872a085 · inbound

The CTLNet for Shanghai Composite Index Prediction cites this paper.

The CTLNet for Shanghai Composite Index Prediction MSHyper: Multi-Scale Hypergraph Transformer for Long-Range Time Series Forecasting

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-10T07:26:59.324393Z

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=2026-05-10T07:26:47.332728Z digest=sha256:b7216b93f109de1692d09935b223c1a7f48050c69d4ec4faa55a6278af242c5a