Paper Citation Record · LEDGER

Graph Foundation Models for Recommendation: A Comprehensive Survey

As of 21 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2502.08346.

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

pith.paper-citation-record.v1
2502.08346 v3

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:30:26.263938Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

44 of 44 outbound references displayed

verified exact11
verified fuzzy15
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 41b5c26f-31bf-4a47-9493-14e8e4da620e · outbound

This paper cites Knowledge Graphs as Context Sources for LLM-Based Explanations of Learning Recommendations.

Graph Foundation Models for Recommendation: A Comprehensive Survey Knowledge Graphs as Context Sources for LLM-Based Explanations of Learning Recommendations

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:27.143039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fbbb1327-8bf8-4782-8cb2-272ad77154bf · outbound

This paper cites Leverage knowledge graph and large language model for law article recommendation: A case study of chinese criminal law.

Graph Foundation Models for Recommendation: A Comprehensive Survey Leverage knowledge graph and large language model for law article recommendation: A case study of chinese criminal law

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-08-08T05:30:27.107612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 80c3232c-028e-4bd1-820b-79daa6e8627d · outbound

This paper cites Deep neural networks for youtube recom- mendations.

Graph Foundation Models for Recommendation: A Comprehensive Survey Deep neural networks for youtube recom- mendations

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.284843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dee37c6f-f6be-44ac-bf7a-449a08667116 · outbound

This paper cites Towards graph foundation models for personalization.

Graph Foundation Models for Recommendation: A Comprehensive Survey Towards graph foundation models for personalization

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.277147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 54d9d350-c8bb-4444-940f-fdc64650942a · outbound

This paper cites Large Language Model with Graph Convolution for Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Large Language Model with Graph Convolution for Recommendation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.100947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82874af3-a9cd-43cc-9ba3-402885e3c95d · outbound

This paper cites A survey of graph neural networks for recommender systems: Challenges, methods, and directions.

Graph Foundation Models for Recommendation: A Comprehensive Survey A survey of graph neural networks for recommender systems: Challenges, methods, and directions

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.269558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 54076ae1-6ce5-4c93-b363-7fc71cf4c98e · outbound

This paper cites Integrating Large Language Models with Graphical Session-Based Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Integrating Large Language Models with Graphical Session-Based Recommendation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.110157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af0a09a4-24e8-48af-bc7d-0464ed3c8b6c · outbound

This paper cites Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations with Large Language Models.

Graph Foundation Models for Recommendation: A Comprehensive Survey Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations with Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.113221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 337ee39b-85d3-4557-9a6a-6e3a8d1efc19 · outbound

This paper cites Topic-Aware Knowledge Graph with Large Language Models for Interoperability in Recommender Systems.

Graph Foundation Models for Recommendation: A Comprehensive Survey Topic-Aware Knowledge Graph with Large Language Models for Interoperability in Recommender Systems

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:26.903390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1c9b48a2-a988-4e04-b532-68dbf234378e · outbound

This paper cites Hetgcot-rec: Heterogeneous graph-enhanced chain-of- thought llm reasoning for journal recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Hetgcot-rec: Heterogeneous graph-enhanced chain-of- thought llm reasoning for journal recommendation

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-08-08T05:30:26.888110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e03ed27e-8a47-4c51-b334-bfe1e0c09afc · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for lan- guage understanding.

Graph Foundation Models for Recommendation: A Comprehensive Survey Bert: Pre-training of deep bidirectional transformers for lan- guage understanding

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.250786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e48b5388-1f51-4a3d-8f27-67f2664d9da5 · outbound

This paper cites Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.129078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9f66913-ca59-4c03-aafc-173c7ee6e0ee · outbound

This paper cites Graph Foundation Models: Concepts, Opportunities and Challenges.

Graph Foundation Models for Recommendation: A Comprehensive Survey Graph Foundation Models: Concepts, Opportunities and Challenges

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.131507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 103c9088-1dfa-47a1-a73f-fa808ad0ed39 · outbound

This paper cites Triple Modality Fusion: Aligning Visual, Textual, and Graph Data with Large Language Models for Multi-Behavior Recommendations.

Graph Foundation Models for Recommendation: A Comprehensive Survey Triple Modality Fusion: Aligning Visual, Textual, and Graph Data with Large Language Models for Multi-Behavior Recommendations

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.134519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be867918-cf10-45aa-859e-916881187403 · outbound

This paper cites XRec: Large Language Models for Explainable Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey XRec: Large Language Models for Explainable Recommendation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.137458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d3ac786-4a01-4af2-91e9-3a480b524247 · outbound

This paper cites LightLM: A Lightweight Deep and Narrow Language Model for Generative Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey LightLM: A Lightweight Deep and Narrow Language Model for Generative Recommendation

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:26.688357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d42f537e-8d9a-43e9-9074-9288163fddba · outbound

This paper cites Denoising alignment with large language model for rec- ommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Denoising alignment with large language model for rec- ommendation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.241021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2e80e4cd-f68b-4b6b-9cf1-0f150b6e2e55 · outbound

This paper cites Unveiling user preferences: A knowledge graph and llm- driven approach for conversational recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Unveiling user preferences: A knowledge graph and llm- driven approach for conversational recommendation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.147908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9946735e-5520-46bf-862d-924466ac2cb5 · outbound

This paper cites Language models are unsupervised multitask learners.

Graph Foundation Models for Recommendation: A Comprehensive Survey Language models are unsupervised multitask learners

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.232144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ab2bf1d5-11b4-478b-849e-a4d0c8aba4c4 · outbound

This paper cites Representation learning with large language models for recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Representation learning with large language models for recommendation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.222627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d0d927b3-3d3d-472c-91a3-71fece0651b1 · outbound

This paper cites LKPNR: LLM and KG for Personalized News Recommendation Framework.

Graph Foundation Models for Recommendation: A Comprehensive Survey LKPNR: LLM and KG for Personalized News Recommendation Framework

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.157349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54a191fc-47e1-47c7-b2af-aa8d77f7a92a · outbound

This paper cites LLM is Knowledge Graph Reasoner: LLM's Intuition-aware Knowledge Graph Reasoning for Cold-start Sequential Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey LLM is Knowledge Graph Reasoner: LLM's Intuition-aware Knowledge Graph Reasoning for Cold-start Sequential Recommendation

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:26.376375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f1b2cb71-759d-42eb-b082-c793e7737c47 · outbound

This paper cites An Automatic Graph Construction Framework based on Large Language Models for Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey An Automatic Graph Construction Framework based on Large Language Models for Recommendation

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:26.363460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9f796cdc-2c67-4035-bf06-a5c041727b42 · outbound

This paper cites Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.220345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e609610-998d-4e46-8058-24c937c25766 · outbound

This paper cites Mgat: Multimodal graph attention network for rec- ommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Mgat: Multimodal graph attention network for rec- ommendation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.212869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9a36c18f-48aa-4891-a1d5-7f7b7ef0e829 · outbound

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

Graph Foundation Models for Recommendation: A Comprehensive Survey Enhancing Recommender Systems with Large Language Model Reasoning Graphs

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.229628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e04747b-e61f-4e5a-bdb0-5b811caa1eb0 · outbound

This paper cites Enabling Explainable Recommendation in E-commerce with LLM-powered Product Knowledge Graph.

Graph Foundation Models for Recommendation: A Comprehensive Survey Enabling Explainable Recommendation in E-commerce with LLM-powered Product Knowledge Graph

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.232535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3537a0f0-ea30-4c6f-bb6a-8c7c86281386 · outbound

This paper cites LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations.

Graph Foundation Models for Recommendation: A Comprehensive Survey LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.236314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acdafe76-cb5c-4716-bc57-cced593a1da5 · outbound

This paper cites Llmrec: Large language models with graph augmentation for recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey Llmrec: Large language models with graph augmentation for recommendation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.193596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9a6d32e3-eb99-4961-90e0-56fc5919f9ef · outbound

This paper cites A comprehensive survey on graph neural networks.

Graph Foundation Models for Recommendation: A Comprehensive Survey A comprehensive survey on graph neural networks

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.183092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 79e61bca-8ea7-48cb-b22d-364536187c67 · outbound

This paper cites Graph neural networks in recommender systems: a survey.

Graph Foundation Models for Recommendation: A Comprehensive Survey Graph neural networks in recommender systems: a survey

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.173672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 84c37f65-f282-498c-ad68-6f31423bb104 · outbound

This paper cites PALR: Personalization Aware LLMs for Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey PALR: Personalization Aware LLMs for Recommendation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.249126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f15e471-79a9-471e-be07-a94d23580748 · outbound

This paper cites Ac- tions speak louder than words: Trillion-parameter sequen- tial transducers for generative recommendations.

Graph Foundation Models for Recommendation: A Comprehensive Survey Ac- tions speak louder than words: Trillion-parameter sequen- tial transducers for generative recommendations

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.162896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d20ca6a7-f08e-4f5b-8c4a-b93cb0f3e2ba · outbound

This paper cites Robust Recommender System: A Survey and Future Directions.

Graph Foundation Models for Recommendation: A Comprehensive Survey Robust Recommender System: A Survey and Future Directions

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:26.308773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation da70e1ac-af2e-4fa7-a0e0-9ed929517088 · outbound

This paper cites Finerec: Exploring fine-grained sequential recommenda- tion.

Graph Foundation Models for Recommendation: A Comprehensive Survey Finerec: Exploring fine-grained sequential recommenda- tion

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.153077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation adcf5ee8-d515-48ea-ae6c-0d3dc2d4b6b9 · outbound

This paper cites A Survey of Large Language Models.

Graph Foundation Models for Recommendation: A Comprehensive Survey A Survey of Large Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.260203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f85efc6-76fc-45d7-a535-afdaa65bec5a · outbound

This paper cites DynLLM: When Large Language Models Meet Dynamic Graph Recommendation.

Graph Foundation Models for Recommendation: A Comprehensive Survey DynLLM: When Large Language Models Meet Dynamic Graph Recommendation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.263938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 246fe877-16cd-467d-ac54-83e631793a9c · outbound

This paper cites Comprehending Knowledge Graphs with Large Language Models for Recommender Systems.

Graph Foundation Models for Recommendation: A Comprehensive Survey Comprehending Knowledge Graphs with Large Language Models for Recommender Systems

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:26.954870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f922a316-56ed-4bfa-ab02-5c2a157b9432 · outbound

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

Graph Foundation Models for Recommendation: A Comprehensive Survey A Survey of Graph Meets Large Language Model: Progress and Future Directions

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.126376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e4ef08c-8666-4d6b-adcc-b3effcef3119 · outbound

This paper cites Graph learning based recommender systems: A review.

Graph Foundation Models for Recommendation: A Comprehensive Survey Graph learning based recommender systems: A review

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.203715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1caf232b-a618-4c65-b238-5a7f8d5fb6c7 · outbound

This paper cites A Prompting-Based Representation Learning Method for Recommendation with Large Language Models.

Graph Foundation Models for Recommendation: A Comprehensive Survey A Prompting-Based Representation Learning Method for Recommendation with Large Language Models

Reference 2021

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:27.121387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 95a8cbae-1c66-4ea2-8cd7-3efbb68a818a · outbound

This paper cites Enhancing Collaborative Semantics of Language Model-Driven Recommendations via Graph-Aware Learning.

Graph Foundation Models for Recommendation: A Comprehensive Survey Enhancing Collaborative Semantics of Language Model-Driven Recommendations via Graph-Aware Learning

Reference 2023

Resolution: verified exact; local_arxiv, observed 2026-08-08T05:30:26.933559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 68928be0-7fe1-4c99-8e61-7a6cafe679a7 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Graph Foundation Models for Recommendation: A Comprehensive Survey On the Opportunities and Risks of Foundation Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T05:30:26.080175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de7931dc-748e-4b54-ac4a-022317fbc8c3 · outbound

This paper cites Large language models on graphs: A comprehensive survey.IEEE Transactions on Knowledge and Data Engineering ,.

Graph Foundation Models for Recommendation: A Comprehensive Survey Large language models on graphs: A comprehensive survey.IEEE Transactions on Knowledge and Data Engineering ,

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T05:30:27.260651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.