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Paper Citation Record · LEDGER

GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2407.09709.

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

pith.paper-citation-record.v1
2407.09709 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T01:07:10.307507Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T08:57:47.509021Z

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 b56888e6-4404-40e4-9959-1d91e5227be5 · inbound

Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach cites this paper.

Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-11T18:23:10.004172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:23:10.004172Z digest=sha256:c7044502a160ed830c04ccb1e044bf13d1ace005ba01bab93f6aeb20eff19cb0

Observation 36cac483-c98b-4d02-9ba0-b167caf94c5b · inbound

Retrieval-Augmented Generation with Graphs (GraphRAG) cites this paper.

Retrieval-Augmented Generation with Graphs (GraphRAG) GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 212

Resolution
verified exact
arxiv_id, observed 2026-05-18T04:33:39.472056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-18T04:33:39.076517Z digest=sha256:915c8c980ad70fb3eb30a52dabb926848b917e6b6bc362388d442fdf633ebd77

Observation d93c3fcc-1b8a-49f4-9dbd-663d52b3b772 · inbound

Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data cites this paper.

Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-16T01:07:10.307507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T01:07:10.307507Z digest=sha256:fe2b0859270f970a619925996bc6da2c0b54a68407fbae6950867d5f4c96953a

Observation 07b70842-a62d-44a5-87be-b63920e5ca58 · inbound

Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach cites this paper.

Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-04T06:16:57.516579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:16:57.516579Z digest=sha256:2d95506067dc40dba62fb33ef3f51205a029fc46b29e396ea34c94270674e8c7

Observation 602fbea1-4c12-4538-8dc0-a642f7b4be48 · inbound

Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models cites this paper.

Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-22T10:31:25.479585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T10:30:01.910920Z digest=sha256:5cbe5f1ddb948848b22a528a5437964749d37bbe98c609439c981e1fb94be847

Observation 72988ad2-2087-4727-a5ac-d6080f4367e8 · inbound

Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval cites this paper.

Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:13:30.376117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T09:08:48.468564Z digest=sha256:a7c20a01214990fd06402246b735a3660c836a753bc1785777e1cc8029d26f2a

Observation 489119dc-93de-43ad-98a1-d1379d2e228c · inbound

HopRank: Self-Supervised LLM Preference-Tuning on Graphs for Few-Shot Node Classification cites this paper.

HopRank: Self-Supervised LLM Preference-Tuning on Graphs for Few-Shot Node Classification GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:06:18.702693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T06:04:24.381169Z digest=sha256:417e848637335b56b3150f5d2b723b795599d64fff4d1229fd9f7b87fb9b040e

Observation 6a4a3e85-d36d-49c7-b96e-e08bdcfbc8cd · inbound

LoReC: Rethinking Large Language Models for Graph Data Analysis cites this paper.

LoReC: Rethinking Large Language Models for Graph Data Analysis GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:41:02.407600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T05:37:22.677992Z digest=sha256:f2a2b4f3b6d38ad787876a4130c693bc81c3abf3189696cc8faa1e27b85f27cb

Observation 85d01c02-c68e-4908-be6f-2f1c184c17d6 · inbound

Edge-Aware Curvature Modeling for Graph Understanding in Large Language Models cites this paper.

Edge-Aware Curvature Modeling for Graph Understanding in Large Language Models GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-02T15:47:06.051584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T23:35:37.053602Z digest=sha256:a95554d28df900692c29c2bd04e382045a2705c771f31a1f16c2acbc72ebed40

Observation 1dbdb616-6e3b-4225-87b8-24377e42818e · inbound

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs cites this paper.

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs GOFA: A Generative One-For-All Model for Joint Graph Language Modeling

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-03T08:57:47.510589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T10:41:37.290485Z digest=sha256:4a743b4d451ef2f52df45af88c3e3442b006eb3043f077837b59b25f24183281