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Paper Citation Record · LEDGER

Discovering Invariant Rationales for Graph Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2201.12872.

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

pith.paper-citation-record.v1
2201.12872 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:32:26.886068Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T08:17:46.013955Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b71c75d6-1601-4845-b2bb-5c5d8fb1602a · inbound

Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective cites this paper.

Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective Discovering Invariant Rationales for Graph Neural Networks

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-09T11:32:26.886068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:32:26.886068Z digest=sha256:e2f23114da11955040bfa5a24771714a45679b010145bcfc7044c1061b7f7751

Observation 5daa2697-85bf-4ddb-8660-c16a798e59e0 · inbound

Do Explanations Increase the Risk of Decision Logic Leakage? Explanation-Guided Stealing of Graph Models cites this paper.

Do Explanations Increase the Risk of Decision Logic Leakage? Explanation-Guided Stealing of Graph Models Discovering Invariant Rationales for Graph Neural Networks

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T11:14:38.389741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:14:38.389741Z digest=sha256:499070da1cd1c142dc7e197114b2fe92eb23722d9d16b7545ba468352536032b

Observation 1081973c-ca81-41f6-afcc-50400aecb9d0 · inbound

A Recipe for Causal Graph Regression: Confounding Effects Revisited cites this paper.

A Recipe for Causal Graph Regression: Confounding Effects Revisited Discovering Invariant Rationales for Graph Neural Networks

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T21:22:24.790695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:22:24.790695Z digest=sha256:469040914ee446adfc48d1892ca3840aef96b3cd34bf41e6ec37de48b43792e3

Observation f6955993-81bc-42ba-a01e-4e291f6c9498 · inbound

When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate cites this paper.

When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate Discovering Invariant Rationales for Graph Neural Networks

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-03T18:48:42.060780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:48:42.060780Z digest=sha256:1b53cbe1426ffc5bb45afe8fae44d84bc90000aa87dc1d30f30cd735825f509d

Observation 37019dfb-75cc-4d6d-b843-91dba13e9283 · inbound

DSBD: Dual-Aligned Structural Basis Distillation for Graph Domain Adaptation cites this paper.

DSBD: Dual-Aligned Structural Basis Distillation for Graph Domain Adaptation Discovering Invariant Rationales for Graph Neural Networks

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-13T19:38:10.584767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T19:34:21.724329Z digest=sha256:cfb75864591acbaf360d3c9cafb3031368cf7a01ef1c43af776385edb947da64

Observation 59a1eeb8-4a45-44bb-a005-8a28023d393f · inbound

Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization cites this paper.

Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization Discovering Invariant Rationales for Graph Neural Networks

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T07:41:01.643746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T17:00:51.046061Z digest=sha256:cb9c15075d2bdd439be8aac4c9280fe17caa79b7d30b637de37136ed3d60ebbd

Observation 43792937-2f70-42b6-9b33-47e15e392a01 · inbound

Cheeger--Hodge Contrastive Learning for Structurally Robust Graph Representation Learning cites this paper.

Cheeger--Hodge Contrastive Learning for Structurally Robust Graph Representation Learning Discovering Invariant Rationales for Graph Neural Networks

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:51:24.688717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T13:38:30.600152Z digest=sha256:b3534d8f06e44685acfbd99fdf8270dc12f0d7117b3f8d103a8cff262658f8ce

Observation 7e54b03d-1ca6-4311-bb48-a5625eca1e8e · inbound

B-cos GNNs: Faithful Explanations through Dynamic Linearity cites this paper.

B-cos GNNs: Faithful Explanations through Dynamic Linearity Discovering Invariant Rationales for Graph Neural Networks

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-20T07:38:09.274616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T07:36:37.630198Z digest=sha256:6bb408563f097d7b0e9066bf9d67433154fa0176e7f8fce37416f04c5abd87a0

Observation c0e740a2-cf10-47ac-b068-c3e9ece418b4 · inbound

B-cos GNNs: Faithful Explanations through Dynamic Linearity cites this paper.

B-cos GNNs: Faithful Explanations through Dynamic Linearity Discovering Invariant Rationales for Graph Neural Networks

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:55:48.372959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T18:36:38.696506Z digest=sha256:9ddfbaca2c27711f16971423d1d9b8c0adbbd7b8c94e98a925b3cbc3836c4fd9

Observation 517b908d-0263-4dbc-80fd-fe2e09bd80b5 · inbound

Beyond Soft Masks: Hard-Perturbation Mixup Explainer for Robust GNN Explainability cites this paper.

Beyond Soft Masks: Hard-Perturbation Mixup Explainer for Robust GNN Explainability Discovering Invariant Rationales for Graph Neural Networks

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:36:55.590895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T03:10:42.043883Z digest=sha256:0722451627222401095302a1d396e2951a05631073012ebdb9b7e41bd4213ea8

Observation 6c58d23f-8f5e-4249-9a71-d4de40001849 · inbound

Artemis: Anatomy-Resolved inTervention for Eliminating Multimodal NeuroImage confounderS cites this paper.

Artemis: Anatomy-Resolved inTervention for Eliminating Multimodal NeuroImage confounderS Discovering Invariant Rationales for Graph Neural Networks

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T08:17:46.015683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T10:46:17.503537Z digest=sha256:4c56db35a2c8615bffe08078022ea08bad5de9073459a8e0308a9834302fc16e

Observation eb56d278-59e4-4bac-bf20-41dbe9cc4c82 · inbound

OpFlow: Learning Opportunity-Conditioned Choice Potentials for Robust OD Flow Prediction cites this paper.

OpFlow: Learning Opportunity-Conditioned Choice Potentials for Robust OD Flow Prediction Discovering Invariant Rationales for Graph Neural Networks

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-12T04:11:50.269344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T04:11:50.269344Z digest=sha256:9973350a23defa98c0842f49da457aef21d4ac12de9717bc50e7e18955f36df6

Observation 9f9c5ecd-e644-47f1-a665-4d966f0637a7 · inbound

Cross-Resolution Semantic Learning for Graph Domain Adaptation cites this paper.

Cross-Resolution Semantic Learning for Graph Domain Adaptation Discovering Invariant Rationales for Graph Neural Networks

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-03T08:31:24.145916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T08:31:24.145916Z digest=sha256:14b090caed3cbaca198eb4588f2d8342a79f23c6ad8df26017e7e21a66106aee