Paper Citation Record · LEDGER

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning

As of 15 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 3 inbound Pith citation observations for arXiv:2506.10282.

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

pith.paper-citation-record.v1
2506.10282 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:33:14.921087Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T13:26:34.419540Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T09:45:40.708465Z

Reference resolution

36 of 36 outbound references displayed

verified exact0
verified fuzzy8
unresolved28
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b3299d88-8992-4bd4-9bd0-168948c00a9a · outbound

This paper cites Qwen Technical Report.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Qwen Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.767965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 320f47e2-fec9-43b9-ad67-d4e0d8d3ad99 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.774590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e36f890-2b83-4cfa-acaf-04351240b353 · outbound

This paper cites LLaGA: Large Language and Graph Assistant.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning LLaGA: Large Language and Graph Assistant

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.782110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6ae6f79-0a86-400c-9f21-b48cb1a84b9e · outbound

This paper cites Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.787363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5768dc0-4c81-4ab9-a766-9b3c43eb0391 · outbound

This paper cites MLaGA: Multimodal Large Language and Graph Assistant.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning MLaGA: Multimodal Large Language and Graph Assistant

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.792462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21eb2460-aa97-49b9-a4b9-36764da1f156 · outbound

This paper cites Gaugllm: Improving graph contrastive learning for text-attributed graphs with large language models.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Gaugllm: Improving graph contrastive learning for text-attributed graphs with large language models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:33:15.700263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 144097fa-a9ee-493c-b482-114a2f99e0d3 · outbound

This paper cites Imagebind: One embedding space to bind them all.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Imagebind: One embedding space to bind them all

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.802459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fc63316-579d-4d72-b75f-f0573995ca15 · outbound

This paper cites From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language Models.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.806769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f468f60-d1c1-45e0-bb19-34b66375369d · outbound

This paper cites Inductive representation learning on large graphs.Advances in neural information processing systems, 30, 2017.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Inductive representation learning on large graphs.Advances in neural information processing systems, 30, 2017

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.811071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 115c196f-d448-499b-be72-f9758f1abfc9 · outbound

This paper cites Unigraph: Learning a cross-domain graph foundation model from natural language.arXiv e-prints, pages arXiv–2402, 2024.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Unigraph: Learning a cross-domain graph foundation model from natural language.arXiv e-prints, pages arXiv–2402, 2024

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:33:15.664829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bb4da213-ed7b-4853-a663-d8562eea8954 · outbound

This paper cites Unigraph2: Learning a unified embedding space to bind multimodal graphs.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Unigraph2: Learning a unified embedding space to bind multimodal graphs

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:33:15.649073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 117ed74b-6035-494f-9fac-5026aed213b4 · outbound

This paper cites Large language models on graphs: A comprehensive survey.IEEE Transactions on Knowledge and Data Engineering, 2024.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Large language models on graphs: A comprehensive survey.IEEE Transactions on Knowledge and Data Engineering, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:33:15.633623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 02c06f9a-b800-4004-ac93-b1046741737b · outbound

This paper cites Snap datasets: Stanford large network dataset collection.Retrieved December 2021 from http://snap.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Snap datasets: Stanford large network dataset collection.Retrieved December 2021 from http://snap

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:33:15.618380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b506c456-ba7e-4800-8e90-b71db6a7acb0 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.831586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42c0f4e7-0bd0-4110-a0fb-01d06fc962e2 · outbound

This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.835920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f6ab7ef-0d6a-4036-8bbd-4e9ac688648a · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.839993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a8ddeee-fea9-4f68-87bd-6a76c3e564ee · outbound

This paper cites GLBench: A Comprehensive Benchmark for Graph with Large Language Models.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning GLBench: A Comprehensive Benchmark for Graph with Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.844131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b8c21cc-6abf-4c24-9a25-fcd47e89e0d8 · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.848200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd5bd22d-aa79-4db9-9e81-a4c1507c5a73 · outbound

This paper cites Can we soft prompt llms for graph learning tasks? InCompanion Proceedings of the ACM Web Conference 2024, pages 481–484, 2024.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Can we soft prompt llms for graph learning tasks? InCompanion Proceedings of the ACM Web Conference 2024, pages 481–484, 2024

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:33:15.581152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 39639e55-5328-48c9-8ce4-ebeb45d8d456 · outbound

This paper cites GPT-4 Technical Report.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning GPT-4 Technical Report

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.856513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4d2f804-a064-4023-a9fa-b445cf306ca5 · outbound

This paper cites Trustglm: Evaluating the robustness of graphllms against prompt, text, and structure attacks.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Trustglm: Evaluating the robustness of graphllms against prompt, text, and structure attacks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:33:15.566793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5e90fe02-d423-46dc-8763-d69c03c73824 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Learning transferable visual models from natural language supervision

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.865180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70c044e3-0610-4a54-9181-1257f4ae2e50 · outbound

This paper cites A survey of large language models for graphs.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning A survey of large language models for graphs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.868920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef6630cb-f2a9-45c2-95dd-4a3f51c9d3e3 · outbound

This paper cites Rosenblatt.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Rosenblatt

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.872996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9c4201e-08d8-4480-aca5-831583212790 · outbound

This paper cites The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning The graph neural network model.IEEE Transactions on Neural Networks, 20(1):61–80, 2009

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.876946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe2e4b4b-6046-4a5d-b4f6-3da23b887911 · outbound

This paper cites an unresolved cited work.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:33:15.541156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 519635bc-f8bf-42ba-ba6b-75b09cbea931 · outbound

This paper cites Graphgpt: Graph instruction tuning for large language models.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Graphgpt: Graph instruction tuning for large language models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.884574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c647a89-51a4-4136-9576-29035e939128 · outbound

This paper cites Mgat: Multimodal graph attention network for recommendation.Information Processing & Management, 57(5):102277, 2020.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Mgat: Multimodal graph attention network for recommendation.Information Processing & Management, 57(5):102277, 2020

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:33:15.514856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 75952a7c-1ddb-443f-84a8-152f8d4a9f9d · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Gemini: A Family of Highly Capable Multimodal Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.892922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29da4f7e-86b4-43e1-af77-8846d47a92e2 · outbound

This paper cites Graph Attention Networks.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Graph Attention Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.896780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f72f294-ae05-4568-80ea-e6b3502358a0 · outbound

This paper cites Mmgcn: Multi-modal graph convolution network for personalized recommendation of micro- video.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Mmgcn: Multi-modal graph convolution network for personalized recommendation of micro- video

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.900852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dba7a12-53be-498e-ba97-7d97af145f45 · outbound

This paper cites When Graph meets Multimodal: Benchmarking and Meditating on Multimodal Attributed Graphs Learning.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning When Graph meets Multimodal: Benchmarking and Meditating on Multimodal Attributed Graphs Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.904938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74e83e17-cfd8-48b3-99c1-22c5b06dc662 · outbound

This paper cites Language is All a Graph Needs.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Language is All a Graph Needs

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.909196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ba8f4aa-ed63-48d0-a4aa-8ee7e64977b4 · outbound

This paper cites Graphtranslator: Aligning graph model to large language model for open-ended tasks.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Graphtranslator: Aligning graph model to large language model for open-ended tasks

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.913329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85159b38-3f49-42cc-bb53-730a069bf9dc · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.917317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9986844c-a93d-4b75-b648-0177d6f9085e · outbound

This paper cites Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning.

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:14.921087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9223bd7a-ea7b-4ed8-a9fa-4b03dd88e48d · inbound

CAMPA: Efficient and Aligned Multimodal Graph Learning via Decoupled Propagation and Aggregation cites this paper.

CAMPA: Efficient and Aligned Multimodal Graph Learning via Decoupled Propagation and Aggregation Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:57:06.218916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6ccb6deb-07ba-4269-a6c0-cba2717617c9 · inbound

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning cites this paper.

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T09:45:40.709754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d4e2f7f7-b61e-486a-84fc-6b60e4d0b471 · inbound

One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language Models cites this paper.

One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language Models Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-01T13:26:34.419540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.