Paper Citation Record · LEDGER

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers

As of 5 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2510.22555.

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

pith.paper-citation-record.v1
2510.22555 v3

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T04:51:23.281272Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:05:36.742930Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

50 of 50 outbound references displayed

verified exact16
verified fuzzy34
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 939307a0-b8cf-42eb-b8a3-d82132946882 · outbound

This paper cites Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.439019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5b8a9e3d-4e09-4dc7-b251-0891132226c3 · outbound

This paper cites Graph neural networks for social recommendation.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph neural networks for social recommendation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.548310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1ad89659-369e-4528-b3bc-5daa225430e8 · outbound

This paper cites Spatio- temporal attention-based neural network for credit card fraud detection.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Spatio- temporal attention-based neural network for credit card fraud detection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.558378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a1d7f430-0e73-4e14-bde1-8132de232ccb · outbound

This paper cites Molecular generative graph neural networks for drug discovery.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Molecular generative graph neural networks for drug discovery

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.538058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2204f14f-a6ec-4af0-9d39-2b7735583c74 · outbound

This paper cites How Powerful are Graph Neural Networks?.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers How Powerful are Graph Neural Networks?

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-18T04:52:23.396639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6fe8287a-440f-401d-bcf6-5c4cb6a9f2de · outbound

This paper cites Inductive representation learning on large graphs.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Inductive representation learning on large graphs

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.535139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0c096a51-7fc0-47f4-a343-d7f347cd0dae · outbound

This paper cites Graph attention networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph attention networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.543446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 56349039-4c47-45d0-9b6a-f3a4ad882845 · outbound

This paper cites Link prediction based on graph neural net- works.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Link prediction based on graph neural net- works

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.560709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation aa936241-9310-4205-9aed-75d9cb86bebf · outbound

This paper cites An end-to-end deep learning architecture for graph classification.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers An end-to-end deep learning architecture for graph classification

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.572920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3c856282-846f-4cea-99eb-5dcaf711c5a8 · outbound

This paper cites Semi-supervised learning with graph learning-convolutional networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Semi-supervised learning with graph learning-convolutional networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.563088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1694faf4-dda6-4425-a9b2-3d0102bb6192 · outbound

This paper cites Deep Graph Contrastive Representation Learning.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Deep Graph Contrastive Representation Learning

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.393656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ba4e1e53-7f83-437b-be29-21e3d9612524 · outbound

This paper cites Graph contrastive learning with cohesive subgraph awareness.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph contrastive learning with cohesive subgraph awareness

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:22.996889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4f4eece4-fc15-4f62-a910-4060104214f5 · outbound

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

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Gppt: Graph pre-training and prompt tuning to generalize graph neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.556189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0bf79e7f-6998-41f5-87e7-5cefafc1ae4e · outbound

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

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graphprompt: Unifying pre- training and downstream tasks for graph neural networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.588258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d8313e87-a174-4394-9906-62dec19084b0 · outbound

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

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers All in one: Multi-task prompting for graph neural networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.570218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation abb41294-bd52-4b62-9763-055b42475536 · outbound

This paper cites A Unified Graph Selective Prompt Learning for Graph Neural Networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers A Unified Graph Selective Prompt Learning for Graph Neural Networks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.430568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c62f8fbe-9905-45fb-861a-a51da172d089 · outbound

This paper cites Graph contrastive backdoor attacks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph contrastive backdoor attacks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.593252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 65695e8f-2f01-428d-81e5-aec648ac7ea1 · outbound

This paper cites Unnoticeable backdoor attacks on graph neural networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Unnoticeable backdoor attacks on graph neural networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.550824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b9f4ed77-42d8-4361-b8c5-9d5e6f561c10 · outbound

This paper cites Rethinking graph back- door attacks: A distribution-preserving perspective.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Rethinking graph back- door attacks: A distribution-preserving perspective

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.553582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 07c48bd1-c6e8-4a76-98b9-92227b09d21b · outbound

This paper cites Cross- context backdoor attacks against graph prompt learning.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Cross- context backdoor attacks against graph prompt learning

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.523142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a5f8c056-27fd-4e87-9029-25532924062f · outbound

This paper cites Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.420041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 04d2a548-8726-4a9a-9bf6-60e76d80b0ec · outbound

This paper cites Robustness Inspired Graph Backdoor Defense.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Robustness Inspired Graph Backdoor Defense

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.415746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5fb68365-f0fb-42cd-a085-d5567ad91f0d · outbound

This paper cites Understanding graph embedding methods and their applications.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Understanding graph embedding methods and their applications

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.400059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9b86a69d-8009-475f-8f40-d4d5817215ae · outbound

This paper cites Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysis.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysis

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.433893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0b579e07-845a-450d-baf2-9e14851274db · outbound

This paper cites Collective classification in network data.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Collective classification in network data

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.600331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f54bf7c6-4b2b-4bfb-a95c-d8a41ebb14ca · outbound

This paper cites Multi-scale attributed node embedding.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Multi-scale attributed node embedding

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.527839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4d47f7b6-e556-417a-b607-303ccbfca6d1 · outbound

This paper cites Open graph benchmark: Datasets for machine learning on graphs.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Open graph benchmark: Datasets for machine learning on graphs

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.575416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d87e371c-9719-40de-92ae-9ee66cec8b5e · outbound

This paper cites Robustness inspired graph backdoor defense.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Robustness inspired graph backdoor defense

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.532746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d9d1be4c-b855-416e-a7a6-eb159cb6d4c0 · outbound

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

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Semi-Supervised Classification with Graph Convolutional Networks

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-18T04:52:23.442659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 64e9f83b-32e0-43eb-b065-22927b4ab539 · outbound

This paper cites Graph transformer networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph transformer networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.597845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d5f2a881-84c5-49e5-ad0b-78d85883e4c5 · outbound

This paper cites Graph con- trastive learning with augmentations.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph con- trastive learning with augmentations

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.565644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 82318548-fbc9-40a4-9850-9b520501f555 · outbound

This paper cites From canonical correlation analysis to self-supervised graph neural networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers From canonical correlation analysis to self-supervised graph neural networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.590857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 35dbb7a1-30ba-4526-90c1-b8e614380fe4 · outbound

This paper cites Hgprompt: Bridging homo- geneous and heterogeneous graphs for few-shot prompt learning.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Hgprompt: Bridging homo- geneous and heterogeneous graphs for few-shot prompt learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.583076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 366c9c4b-28df-4144-97fe-3d04a5369bd7 · outbound

This paper cites Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.411884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8c25c640-efe1-4bc5-bb22-e06b1ed31980 · outbound

This paper cites Spear: A structure-preserving manipulation method for graph backdoor attacks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Spear: A structure-preserving manipulation method for graph backdoor attacks

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.542396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 812cc8dc-e863-41cf-ae61-e44f13a9021f · outbound

This paper cites Backdoor attacks to graph neural networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Backdoor attacks to graph neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.525553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4c7b773e-4688-4faf-9e61-d47ba7be76ac · outbound

This paper cites Graph backdoor.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph backdoor

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.545723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3577f566-5a4d-4181-8185-ef91cd1246ba · outbound

This paper cites Multigprompt for multi-task pre-training and prompting on graphs.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Multigprompt for multi-task pre-training and prompting on graphs

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.530421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 93ff9430-9c1b-4e62-9ecb-2dd81c155b40 · outbound

This paper cites Hetgpt: Harnessing the power of prompt tuning in pre-trained heterogeneous graph neural networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Hetgpt: Harnessing the power of prompt tuning in pre-trained heterogeneous graph neural networks

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.540307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ed818d40-f666-4efa-84df-97ac85da1f2a · outbound

This paper cites Enhancing graph neural networks with structure-based prompt.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Enhancing graph neural networks with structure-based prompt

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.518087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f95fbbe4-456c-4b5a-adee-92a88c32cbd8 · outbound

This paper cites Prodigy: Enabling in-context learning over graphs.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Prodigy: Enabling in-context learning over graphs

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.595785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4d6b1df3-5900-45f8-98b8-fae165662802 · outbound

This paper cites Backdoor attack and defense on deep learning: A survey.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Backdoor attack and defense on deep learning: A survey

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.585586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 84b80608-151b-4151-bd6c-25d23edf6265 · outbound

This paper cites A comprehensive survey on trustworthy graph neural networks: Privacy, robustness, fairness, and explainability.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers A comprehensive survey on trustworthy graph neural networks: Privacy, robustness, fairness, and explainability

Reference 43

Resolution: verified exact; doi, observed 2026-05-18T04:52:23.002124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 590922d8-1fad-4e0e-bd10-ea05df5ad4f3 · outbound

This paper cites Deep anomaly detection on attributed networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Deep anomaly detection on attributed networks

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.577695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6aa9cd2b-0fb1-4eae-956c-7720a67c4403 · outbound

This paper cites Gnnguard: Defending graph neural networks against adversarial attacks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Gnnguard: Defending graph neural networks against adversarial attacks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.567832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 13e31a62-80cb-4c80-bafe-b1b2a70b30a6 · outbound

This paper cites Robust graph convolutional networks against adversarial attacks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Robust graph convolutional networks against adversarial attacks

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T04:52:23.580377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6d4d458c-d635-46e5-b11f-792ac7fb0ce3 · outbound

This paper cites Graph Prompt Learning: A Comprehensive Survey and Beyond.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph Prompt Learning: A Comprehensive Survey and Beyond

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.404069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2def6544-52ef-452f-a046-982c4d7cc684 · outbound

This paper cites Towards Graph Contrastive Learning: A Survey and Beyond.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Towards Graph Contrastive Learning: A Survey and Beyond

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:52:23.427080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 37be0405-d42e-44e3-ace5-306f69afdf74 · outbound

This paper cites Graph Attention Networks.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Graph Attention Networks

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-05-18T04:52:23.407703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a8cb5996-5c46-4d9e-90cf-c54d5c892bce · outbound

This paper cites Inductive Representation Learning on Large Graphs.

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers Inductive Representation Learning on Large Graphs

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-05-18T04:52:23.423649Z

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Pith citing papers

Observation 9b8d7f62-2c32-4f22-a9ca-aca52da31a8b · inbound

Attacking Graph Foundation Models Through Their Shared Representation cites this paper.

Attacking Graph Foundation Models Through Their Shared Representation Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-01T15:05:36.742930Z

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