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Paper Citation Record · LEDGER

Instance-Aware Graph Prompt Learning

As of 12 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2411.17676.

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

pith.paper-citation-record.v1
2411.17676 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:56:36.819840Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:08:19.174713Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:16:02.750930Z

Reference resolution

54 of 54 outbound references displayed

  • verified exact0
  • verified fuzzy39
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ca82038-a810-4dd7-a92b-1f81c4966bbd · outbound

This paper cites Extractive opinion summarization in quantized transformer spaces.

Instance-Aware Graph Prompt Learning Extractive opinion summarization in quantized transformer spaces

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.660711Z digest=sha256:7563a3080c687c413f50ce91a00d7a31f7eb8efc73101b4050591a8ceb7fcbb0

Observation 29223f66-74e5-4200-9847-88e8bb2eba06 · outbound

This paper cites Beit: Bert pre-training of image transformers.

Instance-Aware Graph Prompt Learning Beit: Bert pre-training of image transformers

Reference 2

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raw_fallback, observed 2026-08-12T11:56:37.288862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.664278Z digest=sha256:87686e5fa7f71099c57be9a6819e4dcbd85a7a4f117280df25f92c32f862028e

Observation 86c5739d-d435-477e-b1db-b01cd2f720be · outbound

This paper cites Vector-quantized input-contextualized soft prompts for natural language understanding.

Instance-Aware Graph Prompt Learning Vector-quantized input-contextualized soft prompts for natural language understanding

Reference 3

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raw_fallback, observed 2026-08-12T11:56:37.279352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.667461Z digest=sha256:2a41cff0dd11698db2f61fab62036281dff89d7979c09829d6601ddfc83ef085

Observation cf712884-c5fa-41ea-92b2-8a3da239d66a · outbound

This paper cites Enhancing graph neural network-based fraud detectors against camouflaged fraudsters.

Instance-Aware Graph Prompt Learning Enhancing graph neural network-based fraud detectors against camouflaged fraudsters

Reference 4

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raw_fallback, observed 2026-08-12T11:56:37.269863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.671083Z digest=sha256:e65713d0542d8cf6cc23bad9b82e117116772ebf799caa977f24efb7b70ce991

Observation a5459a05-eb09-4a5f-8150-0ab6be20442e · outbound

This paper cites Multiscale vision transformers.

Instance-Aware Graph Prompt Learning Multiscale vision transformers

Reference 5

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raw_fallback, observed 2026-08-12T11:56:37.260847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.674280Z digest=sha256:982fcae0fe556ab7a59110045a446e70eece551865b2e70b041c34b88088f692

Observation d2c34d70-e8f5-407f-bdfd-02c6f94ea938 · outbound

This paper cites Graph neural networks for social recommendation.

Instance-Aware Graph Prompt Learning Graph neural networks for social recommendation

Reference 6

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raw_fallback, observed 2026-08-12T11:56:37.253118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.677568Z digest=sha256:b63dd17f0ca7114ba355c56fd46af65aa4cc71dc713552c35b3eb0023c2d93bf

Observation bc016e44-72a5-4a61-95fc-551503830447 · outbound

This paper cites Universal prompt tuning for graph neural networks.

Instance-Aware Graph Prompt Learning Universal prompt tuning for graph neural networks

Reference 7

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raw_fallback, observed 2026-08-12T11:56:37.243957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.681746Z digest=sha256:11a87f9cba83a04ea1720d164038f8dc1ee4f865324a4ad75542149ade7e08e6

Observation fd401f2a-0d9a-4a8b-9ebc-17e0596eb0be · outbound

This paper cites Making Pre-trained Language Models Better Few-shot Learners.

Instance-Aware Graph Prompt Learning Making Pre-trained Language Models Better Few-shot Learners

Reference 8

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no resolver link, observed 2026-08-12T11:56:36.684286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.684286Z digest=sha256:45fd5fb1f2bf7a9228c73034ab578061a195afb812b73897d56a9087871aa68e

Observation 84019a22-8bbb-4e4e-835e-07942c5ca51f · outbound

This paper cites Bellis, A.

Instance-Aware Graph Prompt Learning Bellis, A

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.687696Z digest=sha256:60ce1f46c1a4cf9692360df800181fb050b45149eb67b4a9e304073a9659c9db

Observation 40b17744-a06a-4e9a-9503-8363603a75ba · outbound

This paper cites Quantization.

Instance-Aware Graph Prompt Learning Quantization

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.690803Z digest=sha256:5d3053d14909809896844c301361dc26a04bd0be1d09a8da54e0f94a53a339e8

Observation 726611e7-3619-4823-b345-d40c559022a4 · outbound

This paper cites node2vec: Scalable feature learning for networks.

Instance-Aware Graph Prompt Learning node2vec: Scalable feature learning for networks

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.693408Z digest=sha256:a589fed3fb7f31adfbe0e33c62f72022c016a201d802705ceb59a71d3ddf0188

Observation 8ad4ec56-45e5-40a5-a2a5-9f92d00d59bd · outbound

This paper cites PPT: Pre-trained Prompt Tuning for Few-shot Learning.

Instance-Aware Graph Prompt Learning PPT: Pre-trained Prompt Tuning for Few-shot Learning

Reference 12

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no resolver link, observed 2026-08-12T11:56:36.696323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.696323Z digest=sha256:36096a1b2f1eb03240b4c5618560a941b1703eae3ae8236c9c4691ce7a49b771

Observation 514c3168-b214-4707-9ecd-6b63d9b3b691 · outbound

This paper cites Few-shot graph learning for molecular property prediction.

Instance-Aware Graph Prompt Learning Few-shot graph learning for molecular property prediction

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.207142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.699357Z digest=sha256:9fe70120ab75cd8e81697ba2976c3059bf22488afe3fbc27427d915f3b6e1f60

Observation 41ff7514-5442-4723-b00a-f0d521bffd04 · outbound

This paper cites A deep graph neural network-based mechanism for social recommendations.

Instance-Aware Graph Prompt Learning A deep graph neural network-based mechanism for social recommendations

Reference 14

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raw_fallback, observed 2026-08-12T11:56:37.198460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.702523Z digest=sha256:41e373b01b97360e2a60958b4e5eb15e88d61014a4548978a2975ebab61c446d

Observation 575eaa4c-d0d3-4d7b-ab75-13de9d3e90cf · outbound

This paper cites Inductive representation learning on large graphs.

Instance-Aware Graph Prompt Learning Inductive representation learning on large graphs

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.190418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.705840Z digest=sha256:f2c18604557d6a5551f563998e6ca73fe2b36f6b3e72d7343bb5757c322efc3b

Observation 44db2749-d4db-4555-b72c-23fec72292cc · outbound

This paper cites Strategies for pre-training graph neural networks.

Instance-Aware Graph Prompt Learning Strategies for pre-training graph neural networks

Reference 16

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raw_fallback, observed 2026-08-12T11:56:37.181529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.708470Z digest=sha256:bf5adc8a5e8f18773545d44c6d0326e74ee17e110a456e6af87efef196e150f8

Observation be02c24e-0987-4b7c-9d3c-30701554b6de · outbound

This paper cites Strategies for pre-training graph neural networks.

Instance-Aware Graph Prompt Learning Strategies for pre-training graph neural networks

Reference 17

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raw_fallback, observed 2026-08-12T11:56:37.173042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.711517Z digest=sha256:e06a83c5ccfde4f57a991fb937f911a6f7db361c9fc7b46e3ee720ac891f2da4

Observation b90e845d-266e-4c63-92a6-321b51be16e0 · outbound

This paper cites Open Graph Benchmark: Datasets for Machine Learning on Graphs.

Instance-Aware Graph Prompt Learning Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 18

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unresolved
no resolver link, observed 2026-08-12T11:56:36.714523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.714523Z digest=sha256:ca9847e19483a8346d067c608cdf212e2bca4267a4bb3a4bec385d257e4e8c29

Observation 2b5f071a-edca-4532-b850-5188b57c75f6 · outbound

This paper cites Self-supervised Learning on Graphs: Deep Insights and New Direction.

Instance-Aware Graph Prompt Learning Self-supervised Learning on Graphs: Deep Insights and New Direction

Reference 19

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no resolver link, observed 2026-08-12T11:56:36.717412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.717412Z digest=sha256:df30a70dbff4b67a482eeac2387a1d5b943e5094059354293e6619a4652e5f30

Observation 7c0bd060-46f9-4671-b455-b0c9694317f4 · outbound

This paper cites A Comprehensive Survey on Deep Graph Representation Learning.

Instance-Aware Graph Prompt Learning A Comprehensive Survey on Deep Graph Representation Learning

Reference 20

Resolution
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no resolver link, observed 2026-08-12T11:56:36.721330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.721330Z digest=sha256:b1de130759b29858aa7d033e4ed361ba43b8671db2113aa07760fe3436f29620

Observation 15603b7a-8909-450e-882c-a9d900eb7229 · outbound

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

Instance-Aware Graph Prompt Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 21

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no resolver link, observed 2026-08-12T11:56:36.724786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.724786Z digest=sha256:328d451d59679cd0828653da72e532133d93605cb9b81cf785e09bb2979a99ae

Observation fdd54f70-8b52-4d0f-bc8f-11ad12b0f6db · outbound

This paper cites Variational Graph Auto-Encoders.

Instance-Aware Graph Prompt Learning Variational Graph Auto-Encoders

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T11:56:36.728207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.728207Z digest=sha256:133f7bf0a6eb8e1c799f58317257ca7353257490055b4b870cb0778359c774f6

Observation 9c782a5e-f41b-481c-8e1c-75f0e462c076 · outbound

This paper cites Prefix-tuning: Optimizing continuous prompts for generation.

Instance-Aware Graph Prompt Learning Prefix-tuning: Optimizing continuous prompts for generation

Reference 23

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raw_fallback, observed 2026-08-12T11:56:37.164467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.731295Z digest=sha256:5cfdfe19664953bcb0fd039373c4a688aeb67af52bfdf9c405676d6de1f8636e

Observation 6504329b-965e-4061-a041-737294980414 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Instance-Aware Graph Prompt Learning Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 24

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no resolver link, observed 2026-08-12T11:56:36.734339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.734339Z digest=sha256:07ec4e3c7d4429c639b6c92aee3e4aff838a98b46e63c9c95b19b09114194fef

Observation 590b3d37-ee61-4071-8354-b22ca230d485 · outbound

This paper cites One for all: Towards training one graph model for all classification tasks.

Instance-Aware Graph Prompt Learning One for all: Towards training one graph model for all classification tasks

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.153645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.737182Z digest=sha256:52ae435298a06bceaaa30bb26dc6010dcfd2c84f93f8cb40fc5d109ad447cec4

Observation 34b17b8e-0c3c-46f0-8bb0-30bfd41572f7 · outbound

This paper cites Indigo: Gnn-based inductive knowledge graph completion using pair-wise encoding.

Instance-Aware Graph Prompt Learning Indigo: Gnn-based inductive knowledge graph completion using pair-wise encoding

Reference 26

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raw_fallback, observed 2026-08-12T11:56:37.142235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.739766Z digest=sha256:240994c4ed57b768d2a720d7ea86b6eac80e950be54be273621079c2e4cf73ca

Observation fb86cf37-ae06-4c05-9dc1-11c4b021d722 · outbound

This paper cites P -tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks.

Instance-Aware Graph Prompt Learning P -tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.132523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.742663Z digest=sha256:560e9139e9d78e38bff9070cfd3f5c2535c89213380303191e1557e20fd8b075

Observation be4f525c-afdc-4a59-9a88-b6988aabffba · outbound

This paper cites P-tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks.

Instance-Aware Graph Prompt Learning P-tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.124007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.747137Z digest=sha256:fc96be9d7d195839c9a8e5f379ca7a4c39d220ec250ec8d4b74743ad8d65e4f8

Observation b0da9a74-1432-4e12-ba19-057048b7a606 · outbound

This paper cites Pick and choose: A gnn-based imbalanced learning approach for fraud detection.

Instance-Aware Graph Prompt Learning Pick and choose: A gnn-based imbalanced learning approach for fraud detection

Reference 29

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raw_fallback, observed 2026-08-12T11:56:37.115286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.749854Z digest=sha256:caa96db4fd8291350f120e0180885ab961dda4a097459a4670c9dd4069068e4b

Observation 68895dbc-ce07-4fba-94b3-d1538a9695fc · outbound

This paper cites Content matters: a gnn-based model combined with text semantics for social network cascade prediction.

Instance-Aware Graph Prompt Learning Content matters: a gnn-based model combined with text semantics for social network cascade prediction

Reference 30

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raw_fallback, observed 2026-08-12T11:56:37.106502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.752833Z digest=sha256:055cd42aa3e4ef0948b39beb02a92a6bab11637761d27ef4122a8111ecf0fd0b

Observation af6c45b7-fc3f-4538-b6da-130689398c37 · outbound

This paper cites Graphprompt: Unifying pre-training and downstream tasks for graph neural networks.

Instance-Aware Graph Prompt Learning Graphprompt: Unifying pre-training and downstream tasks for graph neural networks

Reference 31

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raw_fallback, observed 2026-08-12T11:56:37.097416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.755456Z digest=sha256:26aa5bccedf04209c075e755bb41d781d0fd144d64e038daa3d458ca8d538689

Observation 1a9a018d-a5fc-4520-b14f-78812456c105 · outbound

This paper cites Large-scale comparison of machine learning methods for drug target prediction on chembl.

Instance-Aware Graph Prompt Learning Large-scale comparison of machine learning methods for drug target prediction on chembl

Reference 32

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raw_fallback, observed 2026-08-12T11:56:37.088448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.757896Z digest=sha256:6577eb3e27e7e5904f7c039279c54f7154b4e93da9c8e4c5bab4bbec37b2da38

Observation 09dbc28a-8002-4374-88a6-59db25a29561 · outbound

This paper cites o f, G \.

Instance-Aware Graph Prompt Learning o f, G \

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.080274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.760749Z digest=sha256:e4ddcf80a9a6d84544f2dd77a59edf868b2bf9aba7c9df8a09308d366cf0a0bd

Observation 3be2a0e9-2306-4306-b6af-200afd43eac7 · outbound

This paper cites Theory and Experiments on Vector Quantized Autoencoders.

Instance-Aware Graph Prompt Learning Theory and Experiments on Vector Quantized Autoencoders

Reference 34

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unresolved
no resolver link, observed 2026-08-12T11:56:36.763409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.763409Z digest=sha256:879d166a2c7f701f37ddcd36fe8a563136ff6fa33317c7514a1081d6930f5b5d

Observation de07ce7c-53c2-46f2-b9c2-1ee4f7c0844a · outbound

This paper cites Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference.

Instance-Aware Graph Prompt Learning Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference

Reference 35

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no resolver link, observed 2026-08-12T11:56:36.766590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.766590Z digest=sha256:0200ee81c396c62cbf31c67cbe1afddb1b3b7173d70cb035fd50ba849a02fc70

Observation 59736880-ef35-4005-9488-a261f57a32d3 · outbound

This paper cites an unresolved cited work.

Instance-Aware Graph Prompt Learning Unresolved cited work

Reference 36

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raw_fallback, observed 2026-08-12T11:56:37.071110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.769689Z digest=sha256:0e891abbaad7b389b46521c6cec61aa4bbafba68f453296615b2e95d68f38e0b

Observation 5075154f-99e7-41f4-913c-6037d1f7c693 · outbound

This paper cites Gppt: Graph pre-training and prompt tuning to generalize graph neural networks.

Instance-Aware Graph Prompt Learning Gppt: Graph pre-training and prompt tuning to generalize graph neural networks

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.060568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.772797Z digest=sha256:2fe628b721c521c7f4dcc33ada4a9de0878274c5ee66acbdfb210be48ad7ffb3

Observation 17dd9e2a-6d12-4493-9dff-628dc9191072 · outbound

This paper cites All in one: Multi-task prompting for graph neural networks.

Instance-Aware Graph Prompt Learning All in one: Multi-task prompting for graph neural networks

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.051928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.775380Z digest=sha256:8dd9a5ac0d7df967604d3cb776a1aea468795402ccebc6174be81d186c82002d

Observation 22a5dd92-4f1d-4ac6-a0d6-cb90a4ba0531 · outbound

This paper cites an unresolved cited work.

Instance-Aware Graph Prompt Learning Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-12T11:56:37.042379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.777864Z digest=sha256:dd956bb658e72f691fab1652c6eac108179ec5ca4b23c6103ab69ef9f6c02ec7

Observation bb9d45bc-eb7c-43c6-8857-1194c6437c5b · outbound

This paper cites Visualizing data using t-sne.

Instance-Aware Graph Prompt Learning Visualizing data using t-sne

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.033433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.780700Z digest=sha256:4ae649c48f9ecbebf431726f310577d677334048a61e239603d4b99d2bc277f9

Observation f30edba6-d49f-44fc-bd77-54977d701d0e · outbound

This paper cites Graph Attention Networks.

Instance-Aware Graph Prompt Learning Graph Attention Networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T11:56:36.783305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.783305Z digest=sha256:7994b6797bf7a9f091ac124d6ea8598dad7bcfdf52aad32003bb3fed54c14fa6

Observation 4c872408-57fb-4dfc-8e3a-1fbfd85b8b4e · outbound

This paper cites Deep graph infomax.

Instance-Aware Graph Prompt Learning Deep graph infomax

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.024818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.786692Z digest=sha256:ce502bb989c21f1322105d9f111f56e8e9b8bf33de79e1e4b53a43583f411401

Observation 52b32dc4-bce7-4431-a1a8-e33b7fd057db · outbound

This paper cites Moleculenet: a benchmark for molecular machine learning.

Instance-Aware Graph Prompt Learning Moleculenet: a benchmark for molecular machine learning

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.015514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.789389Z digest=sha256:7473dbe38970695aea7eab95fe846b02258ce2c11cd2630072fa9e445a82308f

Observation 6047e5ad-dbbe-422a-8bc4-65eeafae8a33 · outbound

This paper cites Simgrace: A simple framework for graph contrastive learning without data augmentation.

Instance-Aware Graph Prompt Learning Simgrace: A simple framework for graph contrastive learning without data augmentation

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:37.006229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.792326Z digest=sha256:1874bc3839dce38cfdeefa77179382089fcaa9b5955516be049dbadc716d7164

Observation d79f3db1-9fda-4618-a8fb-035b6e3d5a9f · outbound

This paper cites How powerful are graph neural networks? In ICLR, 2018.

Instance-Aware Graph Prompt Learning How powerful are graph neural networks? In ICLR, 2018

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T11:56:36.795045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.795045Z digest=sha256:a5a388f212aa0352e61261c1bc0493f024458cd4e9d8663618503c8f574d5746

Observation feb6627c-4043-4ba6-ad35-b5e308f024ac · outbound

This paper cites Revisiting semi-supervised learning with graph embeddings.

Instance-Aware Graph Prompt Learning Revisiting semi-supervised learning with graph embeddings

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:36.992724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.798346Z digest=sha256:4beff5688df3ed6181e905431ff63da5ea3fa66feef2ff32f76bce6635599a67

Observation 10b1a074-a73c-423f-a15a-544314292044 · outbound

This paper cites A comprehensive survey of graph neural networks for knowledge graphs.

Instance-Aware Graph Prompt Learning A comprehensive survey of graph neural networks for knowledge graphs

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:36.983037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.800953Z digest=sha256:f2f7f005b139d9e8200f6c39b0930436f642d0605ac12ae0d031bcb5b38b05d2

Observation 4b7a9462-60cf-4df7-af72-9e14fc7ea0db · outbound

This paper cites Graph contrastive learning with augmentations.

Instance-Aware Graph Prompt Learning Graph contrastive learning with augmentations

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:36.972963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.803691Z digest=sha256:a0cde28cda8afba1c22232a4ea5a3625bdd37822719b1c9b23ae709d7a77a171

Observation 70441fcc-c42b-4114-aeeb-dc069f77f506 · outbound

This paper cites Graph contrastive learning with augmentations.

Instance-Aware Graph Prompt Learning Graph contrastive learning with augmentations

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:36.963301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.806203Z digest=sha256:75a4662f4a4b1c5d7c755feb756d97c48c79cf51445c6988a3c0533b596e3c16

Observation 78a7ef28-4cd6-4996-9ac4-d83a02a7e1cc · outbound

This paper cites Graph transformer networks.

Instance-Aware Graph Prompt Learning Graph transformer networks

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:36.954851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.809161Z digest=sha256:09c16709447fb1ed7fbfd44d86696fae0cceb50844c1ded5573fb722b9b4bf45

Observation 46078f27-f64d-4811-9081-79f4d853aeaf · outbound

This paper cites Graph transformer networks.

Instance-Aware Graph Prompt Learning Graph transformer networks

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:36.946571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.812002Z digest=sha256:091373986805630c3b22e5acfcdb50983756b693adc1083a15fb6055acc1cae9

Observation b5e5c53c-d51a-4b57-9570-b72ad7a24cad · outbound

This paper cites Beyond fully-connected layers with quaternions: Parameterization of hypercomplex multiplications with 1/n parameters.

Instance-Aware Graph Prompt Learning Beyond fully-connected layers with quaternions: Parameterization of hypercomplex multiplications with 1/n parameters

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:36.937831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.814762Z digest=sha256:65b2b5ef478bc31094ad5d2d81eaa457affa04ff28254bbfc5377f9712bdcdb4

Observation 9687f69f-9957-4587-8b0b-0a6624cb214a · outbound

This paper cites Graph contrastive learning with adaptive augmentation.

Instance-Aware Graph Prompt Learning Graph contrastive learning with adaptive augmentation

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:56:36.928291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:56:36.817364Z digest=sha256:107c2d5e6dc56620575f3716c39606389be1f2569259fa4237cc555ea21e1ae9

Observation 504c79af-3172-412e-bedc-32fc38f75566 · outbound

This paper cites write newline.

Instance-Aware Graph Prompt Learning write newline

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-12T11:56:36.819840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:56:36.819840Z digest=sha256:ee4ca6afcff9bbed37c4a446cfa98c80b1032c6f3965ba3607bd3e93acc3616e

Pith citing papers

Observation 7f92f6c7-83a2-4169-9217-228dd05d6367 · inbound

Unified Graph Prompt Learning via Low-Rank Graph Message Prompting cites this paper.

Unified Graph Prompt Learning via Low-Rank Graph Message Prompting Instance-Aware Graph Prompt Learning

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:16:02.758050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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