Paper Citation Record · LEDGER

Out-of-Distribution Detection on Graphs: A Survey

As of 23 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 4 inbound Pith citation observations for arXiv:2502.08105.

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

pith.paper-citation-record.v1
2502.08105 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:29:40.887323Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T00:07:39.525278Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T09:45:40.710826Z

Reference resolution

46 of 46 outbound references displayed

verified exact0
verified fuzzy40
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 234138e1-c635-4dac-8855-5738253172dd · outbound

This paper cites Graph out-of- distribution detection goes neighborhood shaping.

Out-of-Distribution Detection on Graphs: A Survey Graph out-of- distribution detection goes neighborhood shaping

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.724244Z

Source-reported events for the cited work

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Observation 6547e2a4-f394-4f5e-9e17-986195c86f87 · outbound

This paper cites SGOOD: Substructure-enhanced graph-level out- of-distribution detection.

Out-of-Distribution Detection on Graphs: A Survey SGOOD: Substructure-enhanced graph-level out- of-distribution detection

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.668502Z

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Observation 781310c2-2ccf-4c3e-82e6-ac483ec1994e · outbound

This paper cites When and how does in-distribution label help out-of- distribution detection? In ICML,.

Out-of-Distribution Detection on Graphs: A Survey When and how does in-distribution label help out-of- distribution detection? In ICML,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.654541Z

Source-reported events for the cited work

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Observation b128efbc-870b-462d-b0db-c8816bdd36d4 · outbound

This paper cites Graph anomaly detection via multi-scale contrastive learn- ing networks with augmented view.

Out-of-Distribution Detection on Graphs: A Survey Graph anomaly detection via multi-scale contrastive learn- ing networks with augmented view

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.639385Z

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Observation 0f3dbed0-bd86-4cad-afe1-2f141fc90aa6 · outbound

This paper cites Al- leviating structural distribution shift in graph anomaly de- tection.

Out-of-Distribution Detection on Graphs: A Survey Al- leviating structural distribution shift in graph anomaly de- tection

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.624673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 78d994af-3501-4e7f-b2c4-465f8072f068 · outbound

This paper cites An energy-centric framework for category-free out-of- distribution node detection in graphs.

Out-of-Distribution Detection on Graphs: A Survey An energy-centric framework for category-free out-of- distribution node detection in graphs

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.609824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1e544faa-2f34-41fd-bc42-f37fdd74eee3 · outbound

This paper cites GOOD: A graph out-of-distribution bench- mark.

Out-of-Distribution Detection on Graphs: A Survey GOOD: A graph out-of-distribution bench- mark

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.594690Z

Source-reported events for the cited work

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Observation 6729bfa4-ce41-41c0-b85a-069bb8627fc6 · outbound

This paper cites Improvements on uncertainty quantification for node classification via distance based regularization.

Out-of-Distribution Detection on Graphs: A Survey Improvements on uncertainty quantification for node classification via distance based regularization

Reference 13

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Observation 6863eb86-0a87-44c1-842a-5398264ad094 · outbound

This paper cites Open-world lifelong graph learning.

Out-of-Distribution Detection on Graphs: A Survey Open-world lifelong graph learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.553095Z

Source-reported events for the cited work

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Observation e7804cd6-fd06-415b-a682-6b8e2d7aee17 · outbound

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

Out-of-Distribution Detection on Graphs: A Survey Open graph benchmark: Datasets for machine learning on graphs

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.539381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d703f069-f816-42c1-a5f2-4ed7a4ee3299 · outbound

This paper cites DrugOOD: Out-of- distribution dataset curator and benchmark for ai-aided drug discovery–a focus on affinity prediction problems with noise annotations.

Out-of-Distribution Detection on Graphs: A Survey DrugOOD: Out-of- distribution dataset curator and benchmark for ai-aided drug discovery–a focus on affinity prediction problems with noise annotations

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.511873Z

Source-reported events for the cited work

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Observation b098317a-5226-470c-9908-57fa103351cf · outbound

This paper cites A survey of graph neural net- works in real world: Imbalance, noise, privacy and OOD challenges.

Out-of-Distribution Detection on Graphs: A Survey A survey of graph neural net- works in real world: Imbalance, noise, privacy and OOD challenges

Reference 18

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Source-reported events for the cited work

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Observation 549e4e8f-933c-4399-8068-50a72e919f84 · outbound

This paper cites HGOE: Hybrid external and internal graph outlier expo- sure for graph out-of-distribution detection.

Out-of-Distribution Detection on Graphs: A Survey HGOE: Hybrid external and internal graph outlier expo- sure for graph out-of-distribution detection

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.497330Z

Source-reported events for the cited work

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Observation 53e0ce7d-c2a3-449a-a332-c57fa6994e08 · outbound

This paper cites Neural relation graph: A unified frame- work for identifying label noise and outlier data.

Out-of-Distribution Detection on Graphs: A Survey Neural relation graph: A unified frame- work for identifying label noise and outlier data

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.482876Z

Source-reported events for the cited work

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Observation fce61a9c-6d11-47bd-9f64-119ddaba7f28 · outbound

This paper cites Predicting dynamic embedding trajectory in temporal interaction networks.

Out-of-Distribution Detection on Graphs: A Survey Predicting dynamic embedding trajectory in temporal interaction networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.468893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f31ba125-93be-4330-b255-bb4199f010de · outbound

This paper cites Graph neural stochastic diffusion for estimating uncertainty in node classification.

Out-of-Distribution Detection on Graphs: A Survey Graph neural stochastic diffusion for estimating uncertainty in node classification

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.440171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0aafa4e0-52b8-41e4-b6b6-8feb2adc29dc · outbound

This paper cites GOOD-D: On unsupervised graph out-of- distribution detection.

Out-of-Distribution Detection on Graphs: A Survey GOOD-D: On unsupervised graph out-of- distribution detection

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.423925Z

Source-reported events for the cited work

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Observation 0942c0f1-b9fb-4e58-9950-536441d9252a · outbound

This paper cites Towards semi-supervised univer- sal graph classification.

Out-of-Distribution Detection on Graphs: A Survey Towards semi-supervised univer- sal graph classification

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.408776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b1da4b13-b657-4db7-9c78-3bd375783d64 · outbound

This paper cites Revisiting score propagation in graph out-of-distribution detection.

Out-of-Distribution Detection on Graphs: A Survey Revisiting score propagation in graph out-of-distribution detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.394447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 59327200-7a62-480d-a446-28caf6d50e31 · outbound

This paper cites [McAuley et al., 2015] Julian McAuley, Rahul Pandey, and Jure Leskovec.

Out-of-Distribution Detection on Graphs: A Survey [McAuley et al., 2015] Julian McAuley, Rahul Pandey, and Jure Leskovec

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.380065Z

Source-reported events for the cited work

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Observation fedad9d4-2722-4882-8a4d-72ec731327f3 · outbound

This paper cites Collective classification in network data.

Out-of-Distribution Detection on Graphs: A Survey Collective classification in network data

Reference 30

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Source-reported events for the cited work

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Observation 9950f7cf-c065-4be7-b450-80bb12f5ad63 · outbound

This paper cites Calibrate graph neural networks under out-of-distribution nodes via deep Q-learning.

Out-of-Distribution Detection on Graphs: A Survey Calibrate graph neural networks under out-of-distribution nodes via deep Q-learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.326145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e1fdd376-c0dc-4762-a1f0-ab44fc825496 · outbound

This paper cites Learn- ing on graphs with out-of-distribution nodes.

Out-of-Distribution Detection on Graphs: A Survey Learn- ing on graphs with out-of-distribution nodes

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.312036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f411d275-7654-4bf0-81f6-402bb51cc684 · outbound

This paper cites Graph posterior network: Bayesian predic- tive uncertainty for node classification.

Out-of-Distribution Detection on Graphs: A Survey Graph posterior network: Bayesian predic- tive uncertainty for node classification

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.297660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 77f3bcf4-5461-4d8d-a3cb-a32964a3b546 · outbound

This paper cites ArnetMiner: Extraction and mining of academic social networks.

Out-of-Distribution Detection on Graphs: A Survey ArnetMiner: Extraction and mining of academic social networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.283214Z

Source-reported events for the cited work

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Observation e4a003c7-0e6f-415f-9f96-edf3924f4320 · outbound

This paper cites Rethinking graph neural networks for anomaly de- tection.

Out-of-Distribution Detection on Graphs: A Survey Rethinking graph neural networks for anomaly de- tection

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.268031Z

Source-reported events for the cited work

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Observation e45b4cbf-8cb7-45c0-b9db-1f737f8acc83 · outbound

This paper cites Spreading out-of- distribution detection on graphs.

Out-of-Distribution Detection on Graphs: A Survey Spreading out-of- distribution detection on graphs

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.253184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9ec30e9f-bec5-452c-b116-cc4fe764700f · outbound

This paper cites Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark.

Out-of-Distribution Detection on Graphs: A Survey Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark

Reference 39

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Source-reported events for the cited work

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Observation cbedbc88-ef18-4eca-b2d4-ed97ac05bfa9 · outbound

This paper cites GOLD: Graph out-of-distribution de- tection via implicit adversarial latent generation.

Out-of-Distribution Detection on Graphs: A Survey GOLD: Graph out-of-distribution de- tection via implicit adversarial latent generation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.238995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3fbc01fe-e78c-46cb-ade7-03424c815c68 · outbound

This paper cites OpenWGL: Open-world graph learning.

Out-of-Distribution Detection on Graphs: A Survey OpenWGL: Open-world graph learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.224220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 07646bb5-c0cb-4df1-8c02-d6e816ebfa2f · outbound

This paper cites Energy-based out-of-distribution detec- tion for graph neural networks.

Out-of-Distribution Detection on Graphs: A Survey Energy-based out-of-distribution detec- tion for graph neural networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.208536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation be7892f0-2fd3-4c63-875b-a7f64cbf6755 · outbound

This paper cites [Zhang et al., 2022] Qin Zhang, Qincai Li, Xiaojun Chen, Peng Zhang, Shirui Pan, Philippe Fournier-Viger, and Joshua Zhexue Huang.

Out-of-Distribution Detection on Graphs: A Survey [Zhang et al., 2022] Qin Zhang, Qincai Li, Xiaojun Chen, Peng Zhang, Shirui Pan, Philippe Fournier-Viger, and Joshua Zhexue Huang

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.195093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c57c87bb-cb9b-45d1-a8a6-e72d6a0404e8 · outbound

This paper cites Uncertainty aware semi-supervised learning on graph data.

Out-of-Distribution Detection on Graphs: A Survey Uncertainty aware semi-supervised learning on graph data

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.181013Z

Source-reported events for the cited work

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Observation 237e72fa-d35d-49ec-b880-39e2a5634734 · outbound

This paper cites Well- classified examples are underestimated in classification with deep neural networks.

Out-of-Distribution Detection on Graphs: A Survey Well- classified examples are underestimated in classification with deep neural networks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.166741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2d2f05bb-ba71-4e07-abcb-25e50913fd83 · outbound

This paper cites FocusedCleaner: Sanitizing poi- soned graphs for robust GNN-based node classification.

Out-of-Distribution Detection on Graphs: A Survey FocusedCleaner: Sanitizing poi- soned graphs for robust GNN-based node classification

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.151707Z

Source-reported events for the cited work

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Observation cdb702aa-c147-4576-88e0-f7394423f4c0 · outbound

This paper cites Pitfalls of Graph Neural Network Evaluation.

Out-of-Distribution Detection on Graphs: A Survey Pitfalls of Graph Neural Network Evaluation

Reference 2008

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Source-reported events for the cited work

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Observation bf5ffc08-553f-42f3-aa69-17ac1f58ffd1 · outbound

This paper cites Uncertainty-aware graph-based multimodal remote sensing detection of out-of-distribution samples.

Out-of-Distribution Detection on Graphs: A Survey Uncertainty-aware graph-based multimodal remote sensing detection of out-of-distribution samples

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.365455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a0a4a4e0-1ee7-4255-8c61-b1344fed42ca · outbound

This paper cites ML- GOOD: Towards multi-label graph out-of-distribution de- tection.

Out-of-Distribution Detection on Graphs: A Survey ML- GOOD: Towards multi-label graph out-of-distribution de- tection

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.696722Z

Source-reported events for the cited work

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Observation ab1ac964-3865-4828-bc04-13af007de1f6 · outbound

This paper cites Optimizing OOD detection in molecular graphs: A novel approach with diffusion mod- els.

Out-of-Distribution Detection on Graphs: A Survey Optimizing OOD detection in molecular graphs: A novel approach with diffusion mod- els

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.341623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 341cef25-746c-40be-bed7-de5fb0b1deb4 · outbound

This paper cites GraphDE: A generative framework for debiased learning and out-of-distribution detection on graphs.

Out-of-Distribution Detection on Graphs: A Survey GraphDE: A generative framework for debiased learning and out-of-distribution detection on graphs

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.454859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fd25a516-aa4f-4ee0-bd3a-b9d3ce5a9379 · outbound

This paper cites End-to-end open-set semi-supervised node classification with out-of-distribution detection.

Out-of-Distribution Detection on Graphs: A Survey End-to-end open-set semi-supervised node classification with out-of-distribution detection

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.525815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0209cd68-72be-4365-9849-30442ba89b4e · outbound

This paper cites Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings.

Out-of-Distribution Detection on Graphs: A Survey Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T10:29:40.815223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 344c290f-eb2a-4044-bce0-f17ac7baf968 · outbound

This paper cites A data-centric framework to endow graph neural networks with out-of- distribution detection ability.

Out-of-Distribution Detection on Graphs: A Survey A data-centric framework to endow graph neural networks with out-of- distribution detection ability

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.580725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 68615283-caff-47f3-a4a7-59447c92a5fe · outbound

This paper cites Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking.

Out-of-Distribution Detection on Graphs: A Survey Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-08T10:29:40.703633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fe2aa5b-ed9f-407c-a5a1-4b63e2f741bf · outbound

This paper cites Evaluating robustness and uncer- tainty of graph models under structural distributional shifts.

Out-of-Distribution Detection on Graphs: A Survey Evaluating robustness and uncer- tainty of graph models under structural distributional shifts

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.710353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d65bf9d6-a362-4315-bc3a-26df91b67aad · outbound

This paper cites Decoupled graph energy-based model for node out-of-distribution de- tection on heterophilic graphs.

Out-of-Distribution Detection on Graphs: A Survey Decoupled graph energy-based model for node out-of-distribution de- tection on heterophilic graphs

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:29:41.682959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 8c1ca82f-8ae7-41ee-9f88-7cc6b15ce692 · inbound

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs cites this paper.

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs Out-of-Distribution Detection on Graphs: A Survey

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T00:07:39.525278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df494268-4436-440d-8b23-a4cf502f4c92 · inbound

When Brain Networks Travel: Learning Beyond Site cites this paper.

When Brain Networks Travel: Learning Beyond Site Out-of-Distribution Detection on Graphs: A Survey

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:46:09.681129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cb318ab2-759e-42a4-9595-bd2fdb25e569 · inbound

CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detection cites this paper.

CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detection Out-of-Distribution Detection on Graphs: A Survey

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-20T06:58:06.092682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6712e882-362d-4f76-aa44-dbb57038baea · inbound

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

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning Out-of-Distribution Detection on Graphs: A Survey

Reference 143

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:45:40.712478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.