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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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:58:00.880184Z digest=sha256:3658197bcd6eb723218f3583eb02f8c2d147e24f7365ed6a00599fb7266fd8f9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:57:59.933208Z digest=sha256:a8937744260e25f636eeffebf8c9b1f20c811d7c689a96a6251f4781a3b88440

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=sha256:747580fce76d2c6323e9b286ecf88879080ef68cccd28d380f0a36bc0dd30833

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:f4835409b1fa02b893834eb48069f11272627d1cd9e0c52d93683b2d0e727221

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=sha256:964758e5988430a365e415151ae23b54262d529e6d37b8e2fc1a67f752d66845

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:58:00.214356Z digest=sha256:e57907a14e7988b39c06957f5976cb1c600e6e01c1c27cf34e5cda891bbc52a9

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=sha256:13be590dd35097c5339d84f2242dfc750fe93e949561c0b387e1a3b359c376ca

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:58:00.526204Z digest=sha256:13e6c06c878b4a4f6b07d0c6904377abd0fc40acacfef306390026e33f88c3af

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:57:59.730074Z digest=sha256:6c1a0efca17f380d26f2efd3b74454848e23161a67691dceae1635a028afcb77

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=sha256:73b7127696a9085c2722a450c7a10bd06751f01e747acc86c1f50800188ab115

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:58:00.330474Z digest=sha256:fe7ece49a40fb7ab5b10a8137171be584b4a826bd4f4d43b16eae860058b6e01

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:58:00.071359Z digest=sha256:ab4f1d504acb1e781de594c8d7bbff807cc75e6e335c5be0adac10b20ff337fb

Pith citing papers

No inbound Pith citation observations are available.