Paper Citation Record · LEDGER

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2502.08353.

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

pith.paper-citation-record.v1
2502.08353 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:29:38.352508Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

verified exact1
verified fuzzy16
unresolved18
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9aaf130f-889d-47b2-8a5d-c3b41e10da1e · outbound

This paper cites Compositional fairness constraints for graph embeddings.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Compositional fairness constraints for graph embeddings

Reference 1

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Observation 1d1d2407-b894-4ee4-95d1-21ef94e17122 · outbound

This paper cites Graph Learning with Localized Neighborhood Fairness.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Graph Learning with Localized Neighborhood Fairness

Reference 5

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Observation 5b2c4000-945a-4126-b371-7405a93ed973 · outbound

This paper cites Networks in biology.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Networks in biology

Reference 8

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Observation fa7a1c90-0270-4b58-a76a-42f3af4ae5de · outbound

This paper cites Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness

Reference 9

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Observation 9847672f-038b-4f05-b7d9-15ea76f10011 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

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Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Unresolved cited work

Reference 12

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Observation d8bfd7b3-6fa3-4947-ad8a-e9e31cfd410f · outbound

This paper cites Verbalized graph representation learn- ing: A fully interpretable graph model based on large lan- guage models throughout the entire process.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Verbalized graph representation learn- ing: A fully interpretable graph model based on large lan- guage models throughout the entire process

Reference 13

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Observation b519d28c-2e8a-4e82-8aa6-a0ab9c720625 · outbound

This paper cites Could graph neural networks learn better molecular representa- tion for drug discovery? a comparison study of descriptor- based and graph-based models.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Could graph neural networks learn better molecular representa- tion for drug discovery? a comparison study of descriptor- based and graph-based models

Reference 14

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Observation 46bb64e3-1b0f-4af7-a3d0-b4b09ae1c918 · outbound

This paper cites Llm-empowered few-shot node classifica- tion on incomplete graphs with real node degrees,.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Llm-empowered few-shot node classifica- tion on incomplete graphs with real node degrees,

Reference 16

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Source-reported events for the cited work

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Observation 72086012-d31f-4e57-8ad0-4a6ff1467ce2 · outbound

This paper cites Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

Reference 17

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Observation b6afb653-27c5-49ea-9f23-ed88c71f1b1a · outbound

This paper cites Learning to drop: Robust graph neural network via topological denoising.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Learning to drop: Robust graph neural network via topological denoising

Reference 18

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Observation 2929ab7b-5a14-4bed-8c8e-7c8407669edb · outbound

This paper cites Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

Reference 19

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Observation f04f360d-0920-487c-8d50-1b21d7f7a501 · outbound

This paper cites CSGDN: Contrastive Signed Graph Diffusion Network for Predicting Crop Gene-phenotype Associations.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy CSGDN: Contrastive Signed Graph Diffusion Network for Predicting Crop Gene-phenotype Associations

Reference 20

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Observation f4b81496-13dc-4d16-b4d2-22ca14672f05 · outbound

This paper cites Learning transferable visual models from nat- ural language supervision.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Learning transferable visual models from nat- ural language supervision

Reference 21

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Observation 81db1826-cea3-46b6-b47c-41e489847c16 · outbound

This paper cites Fairdrop: Biased edge dropout for enhancing fairness in graph representa- tion learning.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Fairdrop: Biased edge dropout for enhancing fairness in graph representa- tion learning

Reference 22

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Observation b327eeab-00f0-4702-8a95-2297eca0a0c6 · outbound

This paper cites A Review on Graph Neural Network Methods in Financial Applications.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy A Review on Graph Neural Network Methods in Financial Applications

Reference 23

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Source-reported events for the cited work

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Observation 0b8425a8-b22a-4229-af49-f04e95072e0c · outbound

This paper cites Enhancing Recommender Systems with Large Language Model Reasoning Graphs.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Enhancing Recommender Systems with Large Language Model Reasoning Graphs

Reference 24

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Observation 98cb18dc-5511-4012-9215-aaf309447f9b · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 25

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Observation fbf5901f-52b0-4875-9aff-75d5fda60af9 · outbound

This paper cites A com- prehensive survey on graph neural networks.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy A com- prehensive survey on graph neural networks

Reference 26

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This paper cites Graph learning: A survey.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Graph learning: A survey

Reference 27

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Observation 48a5b7f8-d027-44e8-a958-e1aed6e64e68 · outbound

This paper cites Review of graph-based hazardous event detection meth- ods for autonomous driving systems.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Review of graph-based hazardous event detection meth- ods for autonomous driving systems

Reference 28

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Observation 2faf9863-7754-46a7-a84f-8cfd23462175 · outbound

This paper cites Graphformers: Gnn- nested transformers for representation learning on textual graph.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Graphformers: Gnn- nested transformers for representation learning on textual graph

Reference 29

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Observation 3cf14cfe-dc3b-472c-936d-65501e5d03f7 · outbound

This paper cites The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision).

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

Reference 30

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This paper cites Fairsin: Achieving fairness in graph neural networks through sensitive information neutralization.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Fairsin: Achieving fairness in graph neural networks through sensitive information neutralization

Reference 31

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Observation 27475f30-36f0-4b83-aa06-042849e733d9 · outbound

This paper cites Trustworthy Graph Neural Networks: Aspects, Methods and Trends.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Trustworthy Graph Neural Networks: Aspects, Methods and Trends

Reference 32

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This paper cites Rsgnn: A model-agnostic ap- proach for enhancing the robustness of signed graph neu- ral networks.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Rsgnn: A model-agnostic ap- proach for enhancing the robustness of signed graph neu- ral networks

Reference 33

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This paper cites Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?

Reference 34

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This paper cites A Survey of Large Language Models.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy A Survey of Large Language Models

Reference 35

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This paper cites Fair graph representation learning via sensitive attribute disentanglement.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Fair graph representation learning via sensitive attribute disentanglement

Reference 36

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Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Language models are few-shot learners

Reference 2019

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Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy GraphLLM: Boosting Graph Reasoning Ability of Large Language Model

Reference 2020

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This paper cites A Survey of Graph Meets Large Language Model: Progress and Future Directions.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy A Survey of Graph Meets Large Language Model: Progress and Future Directions

Reference 2021

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This paper cites Exploring the potential of large language models (llms) in learning on graphs.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Exploring the potential of large language models (llms) in learning on graphs

Reference 2022

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Observation 170915b7-5df3-4f8a-b5fd-fc7355b0e335 · outbound

This paper cites Iterative deep graph learning for graph neural net- works: Better and robust node embeddings.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Iterative deep graph learning for graph neural net- works: Better and robust node embeddings

Reference 2023

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This paper cites A Survey on In-context Learning.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy A Survey on In-context Learning

Reference 2024

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This paper cites Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning.

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning

Reference 2025

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Pith citing papers

No inbound Pith citation observations are available.