Paper Citation Record · LEDGER

AnyGraph: Graph Foundation Model in the Wild

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2408.10700.

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

pith.paper-citation-record.v1
2408.10700 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:21:35.050298Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:09:57.543813Z

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 2a995ac1-8e3d-49a4-a543-34351d6078a8 · inbound

H$^2$GFM: Towards unifying Homogeneity and Heterogeneity on Text-Attributed Graphs cites this paper.

H$^2$GFM: Towards unifying Homogeneity and Heterogeneity on Text-Attributed Graphs AnyGraph: Graph Foundation Model in the Wild

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T05:21:35.050298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a57b62e3-ff3c-4bda-9128-1a933f025342 · inbound

GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning cites this paper.

GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning AnyGraph: Graph Foundation Model in the Wild

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T14:36:36.460904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c4369e1-9954-4a63-b310-704c7fa03a35 · inbound

No Need to Train Your RDB Foundation Model cites this paper.

No Need to Train Your RDB Foundation Model AnyGraph: Graph Foundation Model in the Wild

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T23:33:32.718367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f069c268-b7fa-45c2-a26a-1e6f3f7a8a5b · inbound

Bridging Input Feature Spaces Towards Graph Foundation Models cites this paper.

Bridging Input Feature Spaces Towards Graph Foundation Models AnyGraph: Graph Foundation Model in the Wild

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:41:08.704886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 70f4c9e0-b1d3-4acb-8cf0-50f49596a7a2 · inbound

On the Safety of Graph Representation Learning cites this paper.

On the Safety of Graph Representation Learning AnyGraph: Graph Foundation Model in the Wild

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:21:07.119026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ca36c7cb-dc2d-4099-b78e-acf615c40e49 · inbound

Graph Computation Meets Circuit Algebra: A Task-Aligned Analysis of Graph Neural Networks for Electronic Design Automation cites this paper.

Graph Computation Meets Circuit Algebra: A Task-Aligned Analysis of Graph Neural Networks for Electronic Design Automation AnyGraph: Graph Foundation Model in the Wild

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:11:15.325075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 212c4f1d-52fe-46f5-902f-754e7a72c483 · inbound

When Do Graph Foundation Models Transfer? A Data-Centric Theory cites this paper.

When Do Graph Foundation Models Transfer? A Data-Centric Theory AnyGraph: Graph Foundation Model in the Wild

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:33:15.266752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3d1bcb41-59ba-4abf-b7ca-a57ce823a7be · 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 AnyGraph: Graph Foundation Model in the Wild

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-04T16:09:57.545268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bca15257-d7f8-401d-a7b9-c7b79ea8e25e · inbound

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning cites this paper.

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning AnyGraph: Graph Foundation Model in the Wild

Reference 232

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T09:45:40.601967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8814d22b-29fe-4dc6-893a-623a318023da · inbound

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework cites this paper.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework AnyGraph: Graph Foundation Model in the Wild

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T22:39:09.664742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d51672c7-8eb6-4c23-9a18-d2d90a87d160 · inbound

CHARM: A Multimodal Graph Foundation Model with Hierarchical Context Modeling for Zero-Shot Transfer cites this paper.

CHARM: A Multimodal Graph Foundation Model with Hierarchical Context Modeling for Zero-Shot Transfer AnyGraph: Graph Foundation Model in the Wild

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-01T00:53:53.541358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.