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Paper Citation Record · LEDGER

Best of Both Worlds: Advantages of Hybrid Graph Sequence Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.15671.

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

pith.paper-citation-record.v1
2411.15671 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:09:39.145081Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T19:25:03.728664Z

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 ca56b91e-3bc1-4e50-a2d6-3a71cbb34ace · inbound

Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation cites this paper.

Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation Best of Both Worlds: Advantages of Hybrid Graph Sequence Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-22T19:25:03.730397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T19:24:48.300461Z digest=sha256:aba4a51b3c5a2362ba7dcc2d59e58101c00f6d9b01409615fa51a352bc93bff6

Observation aaff0a70-3544-43d3-af7c-5df79294bc87 · inbound

Are Large Language Models Good Temporal Graph Learners? cites this paper.

Are Large Language Models Good Temporal Graph Learners? Best of Both Worlds: Advantages of Hybrid Graph Sequence Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T11:09:39.145081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:09:39.145081Z digest=sha256:560c741754d4f799825c0a399cbac96323c0abebf2c593f49d6a11079d4a6849