Paper Citation Record · LEDGER

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model

As of 23 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 2 inbound Pith citation observations for arXiv:2412.06849.

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

pith.paper-citation-record.v1
2412.06849 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:23:02.417444Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T22:31:35.772745Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:08:49.789242Z

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy5
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e0013d71-5215-48c4-94a1-0f6c85f251ff · outbound

This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.341587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd918806-c9f7-4040-9aea-3266d981cc79 · outbound

This paper cites One for All: Towards Training One Graph Model for All Classification Tasks.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model One for All: Towards Training One Graph Model for All Classification Tasks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.386192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0893d72-c12e-4d14-953e-ad355ec494d1 · outbound

This paper cites Graph-oriented Instruction Tuning of Large Language Models for Generic Graph Mining.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model Graph-oriented Instruction Tuning of Large Language Models for Generic Graph Mining

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.391506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fed28bff-dc3d-4076-87b8-ed51324df9c1 · outbound

This paper cites Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.396718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f65580f5-cbb2-4bbd-b004-496ef6911e63 · outbound

This paper cites [reverse] xxx.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model [reverse] xxx

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:23:02.899781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4e43efab-25e9-46d0-85b3-954cd51cad2c · outbound

This paper cites cite” or “cited.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model cite” or “cited

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:23:02.865038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4292c712-c048-4a76-a9c9-82cbf7f2090b · outbound

This paper cites Some parameters are loaded from pretrained LLM.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model Some parameters are loaded from pretrained LLM

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:23:02.917145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 312102f4-25c2-4deb-9d9c-95abca31e9ff · outbound

This paper cites title”: “Jane Krakowski.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model title”: “Jane Krakowski

Reference 500

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:23:02.882740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a3492901-0ea2-4d28-8a37-65d23d25aefd · outbound

This paper cites ISBN 0897919653.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model ISBN 0897919653

Reference 1998

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.364304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ccaded2-4c5c-45d0-991c-501ffcefff27 · outbound

This paper cites ISBN 9781605581026.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model ISBN 9781605581026

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.352577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee626179-cae4-4f6c-875f-208486e62391 · outbound

This paper cites GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.369848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90752192-4720-431c-ac44-be7fff05591b · outbound

This paper cites OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.375213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3371ac03-1de0-410c-adb2-5bfe4b28ea41 · outbound

This paper cites Prompt-based Node Feature Extractor for Few-shot Learning on Text-Attributed Graphs.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model Prompt-based Node Feature Extractor for Few-shot Learning on Text-Attributed Graphs

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.380649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03d9ac89-dddc-42fe-8cf5-d079a191ee13 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model Fast Graph Representation Learning with PyTorch Geometric

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.357374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9643fd14-8443-4b73-850f-c8b4dc65ad78 · outbound

This paper cites Freebase: a collab- oratively created graph database for structuring human knowledge.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model Freebase: a collab- oratively created graph database for structuring human knowledge

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:23:02.934285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 57c3dc66-ca82-47ff-baa8-41ae8f515183 · inbound

Lost in Serialization: Invariance and Generalization of LLM Graph Reasoners cites this paper.

Lost in Serialization: Invariance and Generalization of LLM Graph Reasoners GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T22:31:35.772745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1eaf4b1-b014-4c72-901b-e5b7b33e392d · 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 GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-03T19:08:49.790646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.