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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=sha256:7a3d1670ec78ca73dfb6d0e1be956b1b124301d49df2f711af39a8c86597ed20

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:ea254ad356a05e917d66ec11a102234ec690d2f26790b9a7dfa084dc9919be89

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:fed85a424fd81cdf9fcb3663edd202a869bd2ba5037fee18069ca84004e45de2

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:cfdc4a2bcb2caba95457d5218bcb419abd7e1d96d932d1b67b86e9b134ae039f

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:ebfbb7506b25f6645e5e3cfeeae579446dcde99230b9d05dee801bdb10f380cc

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=sha256:98589b8bc3b383b14e00117792d6ad03e93ebdac47a074efd600ffddf05abac4

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:fb5f621aec656a6def7087d44a3e7bc384412976dff12273d50c391de5bc02c3

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=sha256:240ed639e39fd9e79e41fdc604b67e888405f398f4ef9d450a06148d3574fc10

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:b3bc7a026144f0546e1f62fac8b7232949d39c4945ffa6f5bd22798228a8a7fd

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=sha256:89b5f4b6888817804176abac3bdcdf12d1f482f5f228341168ca50f13661537a

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=sha256:44cbab6244edecf60977f9c51353d749dd2024cf1a98295d0af1e5b42e953e79

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:e19667c5eebda973c7619e3673ed0caddaea2f6b62e002227bfaba6abf0b1a5e

Pith citing papers

No inbound Pith citation observations are available.