Paper Citation Record · LEDGER

Discovering Invariant Rationales for Graph Neural Networks

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 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 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:55:27.823363Z

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

verified exact0
verified fuzzy0
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malformed identifier0
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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 1bc7ffe3-361e-4cbd-959f-c7696be940ae · inbound

Heterophilic Graph Neural Networks Optimization with Causal Message-passing cites this paper.

Heterophilic Graph Neural Networks Optimization with Causal Message-passing Discovering Invariant Rationales for Graph Neural Networks

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:27.823363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e28b5d15-d865-4764-9291-c6bb0e03db6b · inbound

Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts cites this paper.

Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts Discovering Invariant Rationales for Graph Neural Networks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T20:43:51.807989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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.

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.

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.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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.

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.