Paper Citation Record · LEDGER

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2406.10727.

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

pith.paper-citation-record.v1
2406.10727 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:06:04.021216Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:08:49.784031Z

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 09e26837-6d45-4c86-af9e-a4a4dc31f4ac · inbound

Homophily Enhanced Graph Domain Adaptation cites this paper.

Homophily Enhanced Graph Domain Adaptation Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:04.021216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fc561c2-db69-444f-ac5d-2db1e0699ccb · 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 Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:21:34.379679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdb416b1-b01c-4ab0-aaa0-f57f29b9d948 · inbound

Towards Text-free Graph Foundation Models: Rethinking Multi-Domain Graph Contrastive Learning cites this paper.

Towards Text-free Graph Foundation Models: Rethinking Multi-Domain Graph Contrastive Learning Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T22:42:26.613689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbf4a9bc-a171-48b3-9dac-a8220da6874b · inbound

PyG 2.0: Scalable Learning on Real World Graphs cites this paper.

PyG 2.0: Scalable Learning on Real World Graphs Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T15:03:07.306476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee8788a0-728d-429b-9275-a0c8b2c97cd2 · 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 Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T14:36:36.359574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a443f57e-d255-4537-be11-d1f882361ed7 · inbound

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach cites this paper.

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T08:46:07.681687Z

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 6ce1fd7c-ccc4-43b0-b797-a67b4c366089 · inbound

On the Safety of Graph Representation Learning cites this paper.

On the Safety of Graph Representation Learning Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:21:07.082969Z

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 0b6554e8-88c9-475b-b2b3-b674444804dd · inbound

SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory cites this paper.

SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-13T04:52:17.364570Z

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 2618cfd1-2946-4006-96dd-e44613348cae · inbound

LLM Features Can Hurt GNNs: Concatenation Interference on Homophilous Graph Benchmarks cites this paper.

LLM Features Can Hurt GNNs: Concatenation Interference on Homophilous Graph Benchmarks Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-03T19:08:49.785774Z

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 9f8df8a5-2d19-424e-af26-e6bca8de2761 · inbound

Attacking Graph Foundation Models Through Their Shared Representation cites this paper.

Attacking Graph Foundation Models Through Their Shared Representation Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-01T15:05:39.623297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33a04f7a-11bb-4c0b-b5b3-e99ba88cd43a · inbound

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation cites this paper.

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T13:29:51.975602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3bb4989-ac69-4ff3-b76e-bdbd23e661e8 · inbound

GABench: A Comprehensive Benchmark for Evaluating LLM Agents on Graph Analysis Tasks cites this paper.

GABench: A Comprehensive Benchmark for Evaluating LLM Agents on Graph Analysis Tasks Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T22:55:33.826338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.