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Paper Citation Record · LEDGER

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design

As of 11 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 3 inbound Pith citation observations for arXiv:2501.15755.

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

pith.paper-citation-record.v1
2501.15755 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:01:38.480706Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:26:42.822550Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T10:31:25.445556Z

Reference resolution

56 of 56 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved54
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d0625980-5a92-49cf-ae62-f171a60002bf · outbound

This paper cites online" 'onlinestring :=.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design online" 'onlinestring :=

Reference 1

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unresolved
no resolver link, observed 2026-08-10T14:01:38.256011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.256011Z digest=sha256:bce8087a8a0b58d20e5415899acb447e6605edd48234763894567afd5385854b

Observation d56c1572-5d38-473f-ac14-01699f534ec4 · outbound

This paper cites write newline.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design write newline

Reference 2

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no resolver link, observed 2026-08-10T14:01:38.261032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.261032Z digest=sha256:809a0baea7649dd70f15d452212f80c8ae4f1b932d8be5f62d6496d7501c8e80

Observation a78ea3e9-fbf5-4a2f-92f0-a2ca62805764 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 3

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unresolved
no resolver link, observed 2026-08-10T14:01:38.265684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.265684Z digest=sha256:ed6ccf735ad870e658e368624500d376019edef106cd8208109504057eb0658c

Observation 126f3c8a-b29e-40f8-af17-250fba39dec9 · outbound

This paper cites LLaGA: Large Language and Graph Assistant.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design LLaGA: Large Language and Graph Assistant

Reference 4

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unresolved
no resolver link, observed 2026-08-10T14:01:38.269750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.269750Z digest=sha256:7d5f048c10ebb1df11b4192171633fa1a414a67240e5338732f7ae925b4cabd0

Observation 7ab766f6-fe88-42f8-a40a-c5144957b985 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.215663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.274015Z digest=sha256:0383da10d15daa39c751e93db269f1a58f49446e7bd03f625f16fe0f1876bb5e

Observation 70f34a8c-0dac-42b7-bc68-c6694da57e26 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.202722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.278499Z digest=sha256:93dbcb9b06a49c822b9e6fe769c326d90f16a66d27d1b64acc586fee6639b112

Observation f05fe4e7-2365-435a-85ca-7b71143b400b · outbound

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

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction

Reference 7

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unresolved
no resolver link, observed 2026-08-10T14:01:38.282649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.282649Z digest=sha256:51fd3a45101b3a17af589591542777b4b2f65cfcdf3867889c27eac07e80e035

Observation c6a4cdcf-edec-43ec-8302-63d2fde424fb · outbound

This paper cites A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning

Reference 8

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verified exact
local_arxiv, observed 2026-08-10T14:01:38.846711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.286998Z digest=sha256:c6174eb134d31042751584a34672d35fb4064553fc754b357bdf6d423507bdc9

Observation 9557b35d-bcf6-45c5-a4c8-ddb856ff6671 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 9

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no resolver link, observed 2026-08-10T14:01:38.291395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.291395Z digest=sha256:15cf9a85c903bd7c8083d792be36759a887e85e94f06a52bfd30aeac16b24e07

Observation 5b53538b-465e-49a6-91a9-e0d8ed1fce36 · outbound

This paper cites A Survey on In-context Learning.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design A Survey on In-context Learning

Reference 10

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unresolved
no resolver link, observed 2026-08-10T14:01:38.295724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.295724Z digest=sha256:fbcf0f9b05a4123ba2abedcbc20d8aac6abf374f17e2960728e7e0e982e31e61

Observation daba6b6c-832e-40dd-9d61-f9b0deec685e · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.299958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.299958Z digest=sha256:a5bcf792b8a3d35299009bd809b5fa53dc007702b4037c6b082ae68e83cb4ba7

Observation 20038020-4422-45fa-ab50-6d9fa9cb091f · outbound

This paper cites UniGLM: Training One Unified Language Model for Text-Attributed Graph Embedding.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design UniGLM: Training One Unified Language Model for Text-Attributed Graph Embedding

Reference 12

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unresolved
no resolver link, observed 2026-08-10T14:01:38.303572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.303572Z digest=sha256:a9763e81cfb9cb0f3bf26b284771b86fbea247a3d5d99a980c85f13206d6fdef

Observation b2586c7f-4a61-4f14-bd85-f06642e5cc92 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.182480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.307727Z digest=sha256:a569910093e9005858aa667476fb7e0ee728788fc0dd76cef0057e113e0f37e3

Observation f600541f-e4c1-4333-847e-2f3600fbd745 · outbound

This paper cites Towards Foundation Models for Knowledge Graph Reasoning.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Towards Foundation Models for Knowledge Graph Reasoning

Reference 14

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unresolved
no resolver link, observed 2026-08-10T14:01:38.311342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.311342Z digest=sha256:0658456f41bf6471fce3085e1ba59b375ec2cee936852b55d2a45983da17ba3f

Observation fede8a8a-4689-4dbd-8c71-e1c86ccdbb8e · outbound

This paper cites Few-Shot Learning with Graph Neural Networks.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Few-Shot Learning with Graph Neural Networks

Reference 15

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unresolved
no resolver link, observed 2026-08-10T14:01:38.315643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.315643Z digest=sha256:3d43f1cd5087892d4beee059ace71f66e614bd97abb87201696723b84a007c43

Observation 8ad08c22-18e3-4b03-9dce-c3790c3d04aa · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 16

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unresolved
no resolver link, observed 2026-08-10T14:01:38.319667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.319667Z digest=sha256:f17acf12a9d507e46b55bd4d6dad26a4fd51f7490112670fbd853436bdc9afe8

Observation 8eefea6b-39b5-4cf6-b22e-7fe74f4685b7 · outbound

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

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking

Reference 17

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unresolved
no resolver link, observed 2026-08-10T14:01:38.323235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.323235Z digest=sha256:8333e8344791ea159728316944180b8f4adc184bafdc3e5cc5fc85804d565507

Observation 29bd8e27-f77a-46c2-ada7-0eabc64754b2 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 18

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unresolved
no resolver link, observed 2026-08-10T14:01:38.327180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.327180Z digest=sha256:0ea11097f29337fb5a482c84eb744962a83ebe40c457662900d39c086f8dc418

Observation 41902a2f-60c2-4372-a151-d94592f98453 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.154693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.332220Z digest=sha256:4bc43b8ab06b86b82751d525d2229b74705ae7696e9cbaeeeccd5ca10f08fba6

Observation fe477f8d-1652-4b84-b8a0-4b9fe62691c0 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.141169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.336096Z digest=sha256:9d07fab3743503c9551f0b88849b5291b21ff3d1b4a704bfa33bf2c7205d7103

Observation f43bdc88-10ea-4482-a11f-44d1cfa83412 · outbound

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

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning

Reference 21

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no resolver link, observed 2026-08-10T14:01:38.340174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.340174Z digest=sha256:1c9ea1534ee5ef09958737c8c96512188388c13fb1dd17b09f07f71fefb3aadb

Observation 90c40a1b-d5fe-4bb6-afda-e72a1b733492 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.124872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.344789Z digest=sha256:62d4efe252ef5ff69c636d2dc7d1f76533d669cce746ffcf94fbf5641cb7ab77

Observation 6ad8b10b-2b0e-4cc8-8d79-fe64f1e1c03c · outbound

This paper cites UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs

Reference 23

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unresolved
no resolver link, observed 2026-08-10T14:01:38.348716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.348716Z digest=sha256:b44db2d8129cc92a0ab20b441542509ed354b1d72e50fb15238a640e04e08f7a

Observation 9924ca5b-2a70-46eb-96fd-cb96712653f6 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.112158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.353333Z digest=sha256:f9db7683f6496d157c888198e6c92a71997582d9774671d5b7f107a1fa8bdff3

Observation 1e37aed3-6b49-4897-bfa5-478cb2003e0b · outbound

This paper cites Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.357242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.357242Z digest=sha256:c2a96f16c822e7fda4e72c939628eca6c31adeb48e1973299e26df41523b71de

Observation 4c42616f-627c-4fe0-b820-22afc4d71b72 · outbound

This paper cites Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?

Reference 26

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unresolved
no resolver link, observed 2026-08-10T14:01:38.362345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.362345Z digest=sha256:2516b729e7ebe668b1fc3eef598a6bb1883d89763b5dbba867e8d976ea69640a

Observation 87735b33-46dc-44c5-b651-625b7ad69607 · outbound

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

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Semi-Supervised Classification with Graph Convolutional Networks

Reference 27

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unresolved
no resolver link, observed 2026-08-10T14:01:38.367512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.367512Z digest=sha256:ba9823bf58fffb1b638771c13b88bc294d1c8616ebb0db79b3ecee9d94c81704

Observation 23354456-214b-4641-af75-728680528246 · outbound

This paper cites Variational Graph Auto-Encoders.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Variational Graph Auto-Encoders

Reference 28

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unresolved
no resolver link, observed 2026-08-10T14:01:38.371542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.371542Z digest=sha256:b0573b57b31272a1fffb618b52628d705f05e118963613e6dd96a201541ca4df

Observation 6dc0e8a8-b383-4aa8-9f20-15810a28efaa · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 29

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unresolved
no resolver link, observed 2026-08-10T14:01:38.375366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.375366Z digest=sha256:6ea93e3bb2aabe8f2492c181825b6a21922a1d31f34529952489e148db69fa2d

Observation c90f943f-39d4-4aae-8706-f57c038bec92 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.099828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.379378Z digest=sha256:715159989a7a4f5575578b82d3f3327132ab31ab406b8d3e25f3268da8d1957e

Observation 1a07c312-cd7e-4fea-bf31-45bc21bc3b10 · outbound

This paper cites Similarity-based Neighbor Selection for Graph LLMs.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Similarity-based Neighbor Selection for Graph LLMs

Reference 31

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unresolved
no resolver link, observed 2026-08-10T14:01:38.382837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.382837Z digest=sha256:49c11872ee9b5530f5b5b7b1d14798336e79dc17853562198bdd0a36893d3795

Observation 4a716554-1d62-470d-9560-5a847fb4f34a · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.087847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.386920Z digest=sha256:9dd37f6a88f610e8964d25393e09b9ad282180e5ec4981115dd89c8ea32c0282

Observation e04eeff8-7628-44a2-8eb9-7805a14bdd1c · outbound

This paper cites MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

Reference 33

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no resolver link, observed 2026-08-10T14:01:38.391047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.391047Z digest=sha256:73eba3a46f06744f84a14b766bedf65a873c7e50a3636704a35ec50ee35d484d

Observation 091adce0-f1aa-467c-b8b4-b87c27a857b6 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.076007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.395016Z digest=sha256:65833f27323147ae98f4c6e8881fd1f42b2c78804a25a65b84403bd8ed4eb677

Observation 52985730-35dc-49d5-b8b5-0a6ef955631a · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 35

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unresolved
no resolver link, observed 2026-08-10T14:01:38.398999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.398999Z digest=sha256:9eb0301e8abb8f09898eb5c0861eb030181ec43a3bb47ea56cc315d0443fa2b6

Observation 16af32ff-fb98-4f7d-9dff-5258e5b015ee · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.052232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.403180Z digest=sha256:29fdd054688fb48f165a0f65514d2a8a78c6c45e3eb68ed393e696aeb49bc0d4

Observation 35c5a9fd-ea6d-44c1-b52f-0c7fd12511a4 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 37

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no resolver link, observed 2026-08-10T14:01:38.406826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.406826Z digest=sha256:b8f3b28af140d56c0ad1d13804601cebc504c0c545e7e7e2a43b1e306965fd9a

Observation 7b54999e-6619-4692-becf-aba23eb6fb65 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.037145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.411205Z digest=sha256:dd364b6f3e81617062b9670957433c5d932d816c510e9892ba1f8db95cd1e84a

Observation bb516fe1-a371-4386-b7be-66ebae81a051 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.414693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.414693Z digest=sha256:4fda9c6897947a253ffd6f261747239d753b7ce741bd0879be6fe6ec94b56d70

Observation 67b5f4a3-cfa3-4413-b8c2-cc7081085222 · outbound

This paper cites Pitfalls of Graph Neural Network Evaluation.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Pitfalls of Graph Neural Network Evaluation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.418528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.418528Z digest=sha256:07896e2080fce1f33fd95d307cba0408d0b7a57ac99e0c915b751c94b189b8f7

Observation 3435521f-c5eb-4530-b13b-a083bc3e386d · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:39.009901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.422596Z digest=sha256:771b93cc256b1e2d4f58647bfdadaab05903a67908dc7d112a570ac068100eca

Observation 1d54e7a8-93d6-4184-a4ed-d1e40d80ac84 · outbound

This paper cites Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-10T14:01:38.591995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.426218Z digest=sha256:490c24e91083ec88067fae9d0c3c3343ace20c66e6997007d7c952ab2e621e31

Observation f8b3edc2-346f-4496-8b72-a8bee3090e39 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:38.995471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.430797Z digest=sha256:051f3d2fa7c9fc372a84efdc276008465bb0c89ca8e616b6f3374c2ce2cfff0d

Observation 50b6a962-676a-4bac-9f65-59322e157719 · outbound

This paper cites Scalable and Adaptive Graph Neural Networks with Self-Label-Enhanced training.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Scalable and Adaptive Graph Neural Networks with Self-Label-Enhanced training

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.434616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.434616Z digest=sha256:b45512ddf116bc04096ac3e86f28ffc0d226c4712ecaa0f643ff0b933962686b

Observation f94d4a18-3395-4f4d-8e89-7f7403299fb6 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:38.982623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.438788Z digest=sha256:ee06ba57d3a6de132fd539a66f14d4cbfbfd1e6a844aa01d380498c8a6244d3b

Observation 2de842d7-c30f-40e5-ae44-c2f2e47b03e6 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:38.970313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.442529Z digest=sha256:5709fc944751c0da51e4dc25dcfe22ed1633d0b543c65a8b8de0303c08693c59

Observation 304568a9-9b20-47cd-ab8f-23a7423dad63 · outbound

This paper cites GraphGPT: Graph Instruction Tuning for Large Language Models.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design GraphGPT: Graph Instruction Tuning for Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.446044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.446044Z digest=sha256:73dd86700b9db4db683c4ed6ad52bf169da4f5bf2fd88c9296b16de209704ab2

Observation 85b8f6a9-9bef-41dc-b3d8-d39d3edcbd48 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:38.956218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.449976Z digest=sha256:51976667845fd6d4812e8e3b899d15ead920dd8815d087e71c644354b1b814ad

Observation ba1103d0-d095-494c-b574-2c8977b17449 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.453497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.453497Z digest=sha256:def46d428bb378657818b4ad090192da0615c00619995ac287a17eb800e22b93

Observation cfebddd2-2348-4dd4-9012-e581c5f1f0d6 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:38.930678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.457270Z digest=sha256:e9b223a415dc6cf633af5f3d859a3f0cea148290c7ee83c6257459e34a031d9f

Observation c9df5b45-45dc-4ae5-bf62-c301a23b1af2 · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.461493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.461493Z digest=sha256:d47ed76a49c13dc32e61e2fa994fc023d61f318c5269043873512e634f34044c

Observation 61fb6d5c-73bd-4ee4-8304-83391569d77e · outbound

This paper cites GraphFM: A Comprehensive Benchmark for Graph Foundation Model.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design GraphFM: A Comprehensive Benchmark for Graph Foundation Model

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.465186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.465186Z digest=sha256:391dbb9020d6dbddf4e11afd01a9c5662b4f370d9b3ba6c30336465063d1f4be

Observation f5efcfbf-398a-43af-b02d-a41b768549c8 · outbound

This paper cites Language is All a Graph Needs.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Language is All a Graph Needs

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.469157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.469157Z digest=sha256:62a035a95af8a60bc1cb425e4651376579d961c09ba4f900bc20663cfe837988

Observation 9079f20b-239d-4919-9926-a4636ac7307d · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:38.905035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.472989Z digest=sha256:7adef6f81152968b100f9b9d4f73136f0ed4e31bad03b95bb4f844bea3e7ab5a

Observation 26af7ce8-df20-47ef-a9b9-0f0c92e95486 · outbound

This paper cites GraphText: Graph Reasoning in Text Space.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design GraphText: Graph Reasoning in Text Space

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:38.476605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:01:38.476605Z digest=sha256:cf4f2e0e42031f49857f7a002a65513635140ca9a950132c10a776283fff4fa3

Observation ff7f7b0a-4929-443c-b651-0d266095b3ad · outbound

This paper cites an unresolved cited work.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:38.887908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:01:38.480706Z digest=sha256:d03e32c9812efdfd6ec1565a97c0b182736d30679d9fb5517c02e0c00ee1c00f

Pith citing papers

Observation ba55a8f8-e5e8-4829-a95b-e08ede781d78 · inbound

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

MLaGA: Multimodal Large Language and Graph Assistant GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T11:26:42.822550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:26:42.822550Z digest=sha256:ef6c7a215fa2cf771e5acda92a893e3ef86824d3d1514bed4132214675509efc

Observation 9ff36a8a-72d3-4e28-bb8e-d0965bf3c5e7 · inbound

Graph-Based Alternatives to LLMs for Human Simulation cites this paper.

Graph-Based Alternatives to LLMs for Human Simulation GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-18T00:50:33.213844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-18T00:47:40.432039Z digest=sha256:16a358b3c57427c4fb4281a2e07969b3219993ad958173eb4d4e9ff6dcdac939

Observation d8f467bb-d25e-4336-83cb-0891520f6f27 · 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 GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-22T10:31:25.447991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-22T10:30:01.910920Z digest=sha256:42844cb294aa0c1f3baf75a57acabdf4f78ef69088af58b5bb54f8f1b595b107