Paper Citation Record · LEDGER

Residual Reweighted Conformal Prediction for Graph Neural Networks

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2506.07854.

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

pith.paper-citation-record.v1
2506.07854 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:32:06.667371Z

measured 27 of 27 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T02:57:52.488144Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

verified exact1
verified fuzzy12
unresolved12
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 139345fd-d018-4ead-a6fc-8e75b3e736ab · outbound

This paper cites an unresolved cited work.

Residual Reweighted Conformal Prediction for Graph Neural Networks Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:32:08.142304Z

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.

Observation f5d39b90-3f13-4df9-b179-7bb43730afd5 · outbound

This paper cites Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction.

Residual Reweighted Conformal Prediction for Graph Neural Networks Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:32:04.952323Z

Source-reported events for the cited work

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Observation 2ca74de7-c74f-4351-8b35-c8bb67bd2005 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Residual Reweighted Conformal Prediction for Graph Neural Networks Semi-Supervised Classification with Graph Convolutional Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:32:05.204889Z

Source-reported events for the cited work

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Observation 9a173f7b-4997-40d7-aafd-a2e94ecf32d4 · outbound

This paper cites Segregation in social networks: Markov bridge models and estimation.

Residual Reweighted Conformal Prediction for Graph Neural Networks Segregation in social networks: Markov bridge models and estimation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:09.284179Z

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.

Observation 4253d542-8115-4272-beda-9d4ac3df7f8e · outbound

This paper cites Conditional Conformal Risk Adaptation.

Residual Reweighted Conformal Prediction for Graph Neural Networks Conditional Conformal Risk Adaptation

Reference 9

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Source-reported events for the cited work

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Observation 9a901d7e-4ef0-4957-8ac4-f515de5c133c · outbound

This paper cites Mitigating Misinformation Spread on Blockchain Enabled Social Media Networks.

Residual Reweighted Conformal Prediction for Graph Neural Networks Mitigating Misinformation Spread on Blockchain Enabled Social Media Networks

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:32:06.930691Z

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.

Observation 5b21207c-33a2-400f-b8e2-8b571de379a5 · outbound

This paper cites NE means noise edge.

Residual Reweighted Conformal Prediction for Graph Neural Networks NE means noise edge

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:07.631676Z

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.

Observation 573b323a-4030-4c36-acdb-ba3169678585 · outbound

This paper cites Graph Attention Networks.

Residual Reweighted Conformal Prediction for Graph Neural Networks Graph Attention Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:32:06.045884Z

Source-reported events for the cited work

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Observation bbb4678b-b7f0-4eac-a804-e6032e927794 · outbound

This paper cites Nopeek: Information leakage reduc- tion to share activations in distributed deep learning.

Residual Reweighted Conformal Prediction for Graph Neural Networks Nopeek: Information leakage reduc- tion to share activations in distributed deep learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:08.736782Z

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.

Observation 9d4f4f0f-50f1-467c-91c9-087758c6475c · outbound

This paper cites Heterogeneous graph attention network.

Residual Reweighted Conformal Prediction for Graph Neural Networks Heterogeneous graph attention network

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:08.496788Z

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.

Observation a6d6ccfa-9c6a-4bf2-b450-e97b3fb83b3c · outbound

This paper cites Assume the graph has n nodes with f features.

Residual Reweighted Conformal Prediction for Graph Neural Networks Assume the graph has n nodes with f features

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:08.292372Z

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.

Observation 77ae7df4-5e07-4553-8f0e-929e8e8e6dde · outbound

This paper cites 6.3 APPENDICES FIGURES 6.3.1 Schematic figure for transductive and inductive settings for link prediction.

Residual Reweighted Conformal Prediction for Graph Neural Networks 6.3 APPENDICES FIGURES 6.3.1 Schematic figure for transductive and inductive settings for link prediction

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:08.045263Z

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.

Observation b33922d9-33bc-47b5-8eeb-9f93d2c60add · outbound

This paper cites an unresolved cited work.

Residual Reweighted Conformal Prediction for Graph Neural Networks Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:32:07.942957Z

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.

Observation 9cf350cf-0f00-43ef-a79b-32bcc850f154 · outbound

This paper cites The probability is over the datagenerating distribution.

Residual Reweighted Conformal Prediction for Graph Neural Networks The probability is over the datagenerating distribution

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:07.828372Z

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.

Observation 2f8cae9d-874c-4a04-aa56-91b8589e0047 · outbound

This paper cites an unresolved cited work.

Residual Reweighted Conformal Prediction for Graph Neural Networks Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:32:07.392398Z

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.

Observation 7a64095e-5399-4686-8a31-b6d96a2f882b · outbound

This paper cites Normalized nonconformity measures for regression con- formal prediction.

Residual Reweighted Conformal Prediction for Graph Neural Networks Normalized nonconformity measures for regression con- formal prediction

Reference 2002

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:09.004721Z

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.

Observation f4f5d9b2-8ac5-4866-ad9b-d72424441bf4 · outbound

This paper cites Adaptive Conformal Inference by Particle Filtering under Hidden Markov Models.

Residual Reweighted Conformal Prediction for Graph Neural Networks Adaptive Conformal Inference by Particle Filtering under Hidden Markov Models

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-07T05:32:05.965613Z

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Observation b1ade2e2-a121-4e8b-a333-ff94e258fcfb · outbound

This paper cites Split Localized Conformal Prediction.

Residual Reweighted Conformal Prediction for Graph Neural Networks Split Localized Conformal Prediction

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T05:32:05.022846Z

Source-reported events for the cited work

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Observation 47580f16-2a83-4aa3-996d-9203b9f8b52a · outbound

This paper cites an unresolved cited work.

Residual Reweighted Conformal Prediction for Graph Neural Networks Unresolved cited work

Reference 2018

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:32:07.745424Z

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.

Observation aa032897-9676-4d5f-9d6e-310d1d58ea3f · outbound

This paper cites Inductive confidence machines for regression.

Residual Reweighted Conformal Prediction for Graph Neural Networks Inductive confidence machines for regression

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:09.132969Z

Source-reported events for the cited work

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Observation 6d579f7c-3489-4952-8c30-4208124e4509 · outbound

This paper cites Transportation networks for research core team.

Residual Reweighted Conformal Prediction for Graph Neural Networks Transportation networks for research core team

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:08.852512Z

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.

Observation d6a84511-a98f-419f-8831-6de1a5b706c3 · outbound

This paper cites Uncertainty Sets for Image Classifiers using Conformal Prediction.

Residual Reweighted Conformal Prediction for Graph Neural Networks Uncertainty Sets for Image Classifiers using Conformal Prediction

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T05:32:04.914311Z

Source-reported events for the cited work

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Observation 1bd8e853-4d6a-4857-91a4-6391ed20db74 · outbound

This paper cites Deep models under the gan: information leakage from collaborative deep learning.

Residual Reweighted Conformal Prediction for Graph Neural Networks Deep models under the gan: information leakage from collaborative deep learning

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:09.626169Z

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.

Observation c3ebab58-5ce0-428c-b057-544fc1e65649 · outbound

This paper cites Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging.

Residual Reweighted Conformal Prediction for Graph Neural Networks Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging

Reference 2023

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Source-reported events for the cited work

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Observation 77e3cd19-aa15-4a9e-a47e-db64ca0278e3 · outbound

This paper cites Bi-level atten- tion graph neural networks.

Residual Reweighted Conformal Prediction for Graph Neural Networks Bi-level atten- tion graph neural networks

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:32:09.461276Z

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.

Observation a3f0c9eb-3005-4ad7-bb21-24010211cefd · outbound

This paper cites Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution.

Residual Reweighted Conformal Prediction for Graph Neural Networks Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution

Reference 2025

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:32:07.173070Z

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.

Pith citing papers

Observation 17be7e6e-de27-4d0f-b15e-e16980c91e18 · inbound

HeAD-CP: Heterophily-Aware Diffused Conformal Prediction Sets for Graph Neural Networks cites this paper.

HeAD-CP: Heterophily-Aware Diffused Conformal Prediction Sets for Graph Neural Networks Residual Reweighted Conformal Prediction for Graph Neural Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T02:57:52.488144Z

Source-reported events for the cited work

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