Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T05:23:48.050833Z
Paper Citation Record · LEDGER
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs
As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2412.17609.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-26T00:50:39.622302Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T16:09:57.525108Z
Reference resolution
12 of 12 outbound references displayed
- verified exact1
- verified fuzzy4
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation cd53cc58-6627-45e5-bfae-5737c4c50c9c · outbound
This paper cites Incidence Networks for Geometric Deep Learning.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Incidence Networks for Geometric Deep Learning
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T05:23:48.296558Z
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.
Observation b251d7a9-98fd-4c41-8938-902529e92bf0 · outbound
This paper cites an unresolved cited work.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Unresolved cited work
Reference 3
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T05:23:48.321120Z
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.
Observation 85c2460c-990a-441e-b51e-d3c6720168f8 · outbound
This paper cites These rep- resentations are linearly transformed by component (d), and then summed along with the encoding of the explicit, original node features in output from component (e).
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs These rep- resentations are linearly transformed by component (d), and then summed along with the encoding of the explicit, original node features in output from component (e)
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T05:23:48.504186Z
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.
Observation 251fc98d-2c88-4f8d-ad7c-fc9e40fbe42e · outbound
This paper cites Text-Free Multi-domain Graph Pre-training: Toward Graph Foundation Models.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Text-Free Multi-domain Graph Pre-training: Toward Graph Foundation Models
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:23:48.030264Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a3816ab5-f8eb-4e8c-bed0-1fe3e1cfb915 · outbound
This paper cites We use the same ‘mae + cosine similarity’ loss (Cant¨ urk et al., 2024).
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs We use the same ‘mae + cosine similarity’ loss (Cant¨ urk et al., 2024)
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T05:23:48.517959Z
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.
Observation 5c598726-704f-4f78-a35a-778ac576a2ad · outbound
This paper cites in-dataset.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs in-dataset
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T05:23:48.308886Z
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.
Observation ac2cc943-8d69-41b5-9b56-a53f1f8015a1 · outbound
This paper cites In accordance with Cant¨ urk et al.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs In accordance with Cant¨ urk et al
Reference 128
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T05:23:48.399645Z
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.
Observation 60b3964c-d267-465d-b708-d4f47381c794 · outbound
This paper cites One for All: Towards Training One Graph Model for All Classification Tasks.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs One for All: Towards Training One Graph Model for All Classification Tasks
Reference 2015
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:23:48.025336Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation afe06e31-0cf0-4566-8f9a-56cff09a9548 · outbound
This paper cites Residual Gated Graph ConvNets.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Residual Gated Graph ConvNets
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:23:48.009572Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0afd902a-f44b-4bb3-aba8-db360e21097d · outbound
This paper cites an unresolved cited work.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Unresolved cited work
Reference 2019
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T05:23:48.530990Z
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.
Observation ce63fd51-d703-4d56-b8cc-8876e7c4bce5 · outbound
This paper cites Benchmarking Graph Neural Networks.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Benchmarking Graph Neural Networks
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:23:48.018034Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62e823d4-89da-4a91-b6cd-fb038210e18e · outbound
This paper cites PRODIGY: Enabling In-context Learning Over Graphs.
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs PRODIGY: Enabling In-context Learning Over Graphs
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:23:48.021354Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation 68fc3f46-578b-49bc-89f3-895a229fe18f · inbound
Bridging Input Feature Spaces Towards Graph Foundation Models cites this paper.
Bridging Input Feature Spaces Towards Graph Foundation Models Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T17:41:08.762109Z
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.
Observation d0a57732-d3d1-49bb-acbf-7351c2c5be14 · inbound
A Fair Evaluation of Graph Foundation Models for Node Property Prediction cites this paper.
A Fair Evaluation of Graph Foundation Models for Node Property Prediction Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T16:09:57.527492Z
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.