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Paper Citation Record · LEDGER

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference

As of 9 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2505.16893.

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

pith.paper-citation-record.v1
2505.16893 v2

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:58:00.880184Z

measured 12 of 12 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

  • verified exact5
  • verified fuzzy2
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 569d60af-5d8b-4447-8ef3-ca81455116da · outbound

This paper cites Other settings were the same as the default settings in the Type I error rate evaluation in Section 6.2.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Other settings were the same as the default settings in the Type I error rate evaluation in Section 6.2

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:58:01.922180Z

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=2026-08-07T14:58:00.880184Z digest=sha256:62e8d8a8163c6eaef6dca0d86fd5d814e69aa51f177c8e92b0bb0d40b0369e05

Observation 69d41bc7-16cd-41e8-af5e-9d117abe674b · outbound

This paper cites Statistical Test for Diffusion-Based Anomaly Localization via Selective Inference.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Statistical Test for Diffusion-Based Anomaly Localization via Selective Inference

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:58:01.673181Z

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=2026-08-07T14:57:59.933208Z digest=sha256:c80c1f5f305cde3c5110d1934587746a5e9f55ff9048933bd6eaef2d68464240

Observation 90d5c817-3b59-43de-ac09-08a9b695a896 · outbound

This paper cites Statistical Test for Anomaly Detections by Variational Auto-Encoders.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Statistical Test for Anomaly Detections by Variational Auto-Encoders

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:58:00.650296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:58:00.650296Z digest=sha256:4d8584188644635ed22e2564ef964c24125aacff502e147ab4800d7307bf01c8

Observation 975959d9-741a-410d-bde7-e211d5f08bc5 · outbound

This paper cites Statistical Test for Feature Selection Pipelines by Selective Inference.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Statistical Test for Feature Selection Pipelines by Selective Inference

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:58:00.710065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:58:00.710065Z digest=sha256:9c2fb924fca6f098e3793d1175f3a69881152655d43bd6a2a572bce3636d08e0

Observation 86877ce7-3e36-4b3f-91e7-8868151dac6d · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:58:00.801546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:58:00.801546Z digest=sha256:7b38d1fef46c0288ff8002ca3b7792b1c6c5649aac33098ddb3ff30ee087b725

Observation b106095f-1615-4e06-b763-574dce272fe3 · outbound

This paper cites Graph Neural Network Explanations are Fragile.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Graph Neural Network Explanations are Fragile

Reference 1986

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:58:01.329014Z

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=2026-08-07T14:58:00.214356Z digest=sha256:7047f0bbbb4b58ebc20b0aa0b38928499e9ae608e0c2873523f4215773007b09

Observation 2a3d44e6-2e72-48d5-9dbf-26b547db33d7 · outbound

This paper cites Unifying approach to selective inference with applications to cross-validation.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Unifying approach to selective inference with applications to cross-validation

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-07T14:58:00.450130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:58:00.450130Z digest=sha256:9eb53947d5628142b0499bb9e180f5da61afbc841b3de0ab529fda7c727d4ec8

Observation 63dfa5e5-3b8a-47fb-86ca-357194b66248 · outbound

This paper cites Statistical Test for Auto Feature Engineering by Selective Inference.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Statistical Test for Auto Feature Engineering by Selective Inference

Reference 2017

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:58:01.087116Z

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=2026-08-07T14:58:00.526204Z digest=sha256:70b74c6a11ae739bcebb92cefabd0e6e01789e7bd86ff70e1d79d0fbe476665b

Observation cc0d6d3f-361f-47fc-be6f-1351b9229f88 · outbound

This paper cites Graphsvx: Shapley value explanations for graph neural networks.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Graphsvx: Shapley value explanations for graph neural networks

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:58:02.207602Z

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=2026-08-07T14:57:59.730074Z digest=sha256:83ca53ffb4e4cc2500afc94bfb7e28f9b72234f3c3d6e84dc866bdbe277e4416

Observation 8129c2e1-3cdc-4824-b029-55eb60e25dfc · outbound

This paper cites Optimal Inference After Model Selection.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference Optimal Inference After Model Selection

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T14:57:59.826922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:57:59.826922Z digest=sha256:9e1816d5507451b4e87beb3866d2b6b2a06505673977c640bf0b5de5b2a774a2

Observation 43c15251-1ffe-41c0-8707-ef57bbeb1c69 · outbound

This paper cites A significance test for forward stepwise model selection.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference A significance test for forward stepwise model selection

Reference 2023

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:58:01.233283Z

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=2026-08-07T14:58:00.330474Z digest=sha256:bf2d679d6d09d40c8c0ad91bb961a5f500b0d0120afa51031f6ea7b436b2496e

Observation a3d54827-3856-4eb7-9ead-a4e9e071774d · outbound

This paper cites si4onnx: A Python package for Selective Inference in Deep Learning Models.

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference si4onnx: A Python package for Selective Inference in Deep Learning Models

Reference 2024

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:58:01.462679Z

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=2026-08-07T14:58:00.071359Z digest=sha256:76ff5313bb54ddfd60d0be7d8adee296b2b651e74cbbca3b05cb454e86cb6f21

Pith citing papers

No inbound Pith citation observations are available.