Pith. sign in

Paper Citation Record · LEDGER

All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.09834.

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

pith.paper-citation-record.v1
2402.09834 v2

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 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:40:13.245479Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:08:56.281916Z

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 ca75ef56-e59e-4266-80f6-86e06b35cd75 · inbound

DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach cites this paper.

DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T14:40:13.245479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:40:13.245479Z digest=sha256:2ed5d819fec2b03ffd06118bbfefb594e5a0284981b4f5340bfefbd5f87ca0fd

Observation cb3097c0-30c2-4d0f-9912-28f3c6a195eb · inbound

Handling Feature Heterogeneity with Learnable Graph Patches cites this paper.

Handling Feature Heterogeneity with Learnable Graph Patches All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:08:56.284154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T01:36:45.977332Z digest=sha256:9dc03e09b7eb078dc60361b08438ac01a211229e71bbd3ba9a44e5361994487d