Paper Citation Record · LEDGER

Graph Structure Learning with Bi-level Optimization

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2411.17062.

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

pith.paper-citation-record.v1
2411.17062 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:41:10.269668Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

31 of 31 outbound references displayed

verified exact0
verified fuzzy25
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c7075ba5-f017-4eb8-82db-2e8d989209c9 · outbound

This paper cites Forward and reverse gradient-based hyperparameter optimization.

Graph Structure Learning with Bi-level Optimization Forward and reverse gradient-based hyperparameter optimization

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.720878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0c757b18-ba20-4091-a716-279675ba8bec · outbound

This paper cites Semi-supervised learning with graph learning-convolutional networks.

Graph Structure Learning with Bi-level Optimization Semi-supervised learning with graph learning-convolutional networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.683134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e8ab9a4b-d7de-442b-8ee3-86b6f430c1c5 · outbound

This paper cites A survey of graph neural net- works in real world: Imbalance, noise, privacy and ood challenges.

Graph Structure Learning with Bi-level Optimization A survey of graph neural net- works in real world: Imbalance, noise, privacy and ood challenges

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T12:41:10.172240Z

Source-reported events for the cited work

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Observation 211fde89-31b3-41f8-b58b-c5347ce23a7a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Graph Structure Learning with Bi-level Optimization Adam: A Method for Stochastic Optimization

Reference 9

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Source-reported events for the cited work

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Observation 809355e4-ddc3-4e26-862d-8f17aef9d5c2 · outbound

This paper cites Understanding attention and gen- eralization in graph neural networks.

Graph Structure Learning with Bi-level Optimization Understanding attention and gen- eralization in graph neural networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.649709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 13303b79-3151-4d8f-b3f1-7e752583861d · outbound

This paper cites Adaptive graph convolutional neural net- works.

Graph Structure Learning with Bi-level Optimization Adaptive graph convolutional neural net- works

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.637211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b52a4411-c2c0-47fc-a2e8-86c92d4d3ff6 · outbound

This paper cites McPherson, L.

Graph Structure Learning with Bi-level Optimization McPherson, L

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.603666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cb7e24c8-4e7d-4228-91cc-1bd16090e624 · outbound

This paper cites The graph neural network model.

Graph Structure Learning with Bi-level Optimization The graph neural network model

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.555679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d3062b9e-d057-49d9-b2e4-a339812bb315 · outbound

This paper cites Graph Attention Networks.

Graph Structure Learning with Bi-level Optimization Graph Attention Networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.543112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a6371a88-527b-4b2d-8f17-d90a2ba6dda9 · outbound

This paper cites Learn- ing node representations from noisy graph structures.

Graph Structure Learning with Bi-level Optimization Learn- ing node representations from noisy graph structures

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.531114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a3f01030-6afb-4863-a7b8-3d7a0dcef8ae · outbound

This paper cites Multi-hop attention graph neu- ral network.

Graph Structure Learning with Bi-level Optimization Multi-hop attention graph neu- ral network

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.518752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 563ca29c-0255-4d8f-8947-a853ab3849dd · outbound

This paper cites Demo- net: Degree-specific graph neural networks for node and graph classification.

Graph Structure Learning with Bi-level Optimization Demo- net: Degree-specific graph neural networks for node and graph classification

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.506499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4b85a48a-4200-457f-9f3f-8fc67fed3a96 · outbound

This paper cites Graph information bottleneck.

Graph Structure Learning with Bi-level Optimization Graph information bottleneck

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.493484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 634db40e-d52b-4c1c-b066-4ff04a660f2b · outbound

This paper cites Representation learning on graphs with jumping knowledge networks.

Graph Structure Learning with Bi-level Optimization Representation learning on graphs with jumping knowledge networks

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.479903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 756713a4-1615-46c5-a296-d0480bf1f584 · outbound

This paper cites Sport: A subgraph perspective on graph classification with label noise.

Graph Structure Learning with Bi-level Optimization Sport: A subgraph perspective on graph classification with label noise

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.467143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6ca3b4b2-de62-4f38-8ad9-0d076f5e3aee · outbound

This paper cites Continuous Spiking Graph Neural Networks.

Graph Structure Learning with Bi-level Optimization Continuous Spiking Graph Neural Networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T12:41:10.256927Z

Source-reported events for the cited work

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Observation e6dc5237-98a6-409f-b9b7-f82b752ada95 · outbound

This paper cites Bayesian graph con- volutional neural networks for semi-supervised classifica- tion.

Graph Structure Learning with Bi-level Optimization Bayesian graph con- volutional neural networks for semi-supervised classifica- tion

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.454331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9e59baf3-30a5-4690-a45c-8ea94266e4a7 · outbound

This paper cites Sen, and L.

Graph Structure Learning with Bi-level Optimization Sen, and L

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.441400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b938cf75-643a-4b61-9db3-695b71fc5b6a · outbound

This paper cites Robust graph representation learning via neural sparsification.

Graph Structure Learning with Bi-level Optimization Robust graph representation learning via neural sparsification

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.427802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 51bfe43d-786f-4e20-9f11-7c36e1729690 · outbound

This paper cites Faloutsos.

Graph Structure Learning with Bi-level Optimization Faloutsos

Reference 2001

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.591596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 63ac1c5b-67fb-427f-b4e2-eed2a526534a · outbound

This paper cites Sa-gda: Spectral augmen- tation for graph domain adaptation.

Graph Structure Learning with Bi-level Optimization Sa-gda: Spectral augmen- tation for graph domain adaptation

Reference 2007

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.579863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d97ee46e-1d80-4443-b7ed-4157a006389f · outbound

This paper cites Adversarial Representation with Intra-Modal and Inter-Modal Graph Contrastive Learning for Multimodal Emotion Recognition.

Graph Structure Learning with Bi-level Optimization Adversarial Representation with Intra-Modal and Inter-Modal Graph Contrastive Learning for Multimodal Emotion Recognition

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-12T12:41:10.224616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8e40245-5fdc-4784-8c95-8e93c20659e5 · outbound

This paper cites Variational inference for graph convolutional networks in the absence of graph data and adversarial set- tings.

Graph Structure Learning with Bi-level Optimization Variational inference for graph convolutional networks in the absence of graph data and adversarial set- tings

Reference 2012

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.737130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f866baba-31c1-47d6-8289-944735b2b5e3 · outbound

This paper cites Kipf and Max Welling.

Graph Structure Learning with Bi-level Optimization Kipf and Max Welling

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-12T12:41:10.184797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daf2fbe5-0367-49e4-8913-b00c63e5fa47 · outbound

This paper cites Learning discrete structures for graph neural networks.

Graph Structure Learning with Bi-level Optimization Learning discrete structures for graph neural networks

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.708209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bbd03db9-037b-462a-b51b-06f7bfffe399 · outbound

This paper cites Learning to drop: Robust graph neural network via topological denoising.

Graph Structure Learning with Bi-level Optimization Learning to drop: Robust graph neural network via topological denoising

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-12T12:41:10.196803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c7b5be9-3681-496a-954a-d4046f5181dd · outbound

This paper cites Hamilton, Rex Ying, and Jure Leskovec.

Graph Structure Learning with Bi-level Optimization Hamilton, Rex Ying, and Jure Leskovec

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.695662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2e7df6a1-85bf-47e8-b0ce-d615a3617e12 · outbound

This paper cites Generic methods for optimization-based modeling.

Graph Structure Learning with Bi-level Optimization Generic methods for optimization-based modeling

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.749924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bd0e07d0-6201-4de8-b535-6b9727038081 · outbound

This paper cites Gradient-based hyperparameter optimization through reversible learning.

Graph Structure Learning with Bi-level Optimization Gradient-based hyperparameter optimization through reversible learning

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.616262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 39736f03-31c0-422f-90ce-59d9d13516af · outbound

This paper cites Dropedge: Towards deep graph con- volutional networks on node classification.

Graph Structure Learning with Bi-level Optimization Dropedge: Towards deep graph con- volutional networks on node classification

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.568072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 54a7e5d8-b3af-41d8-829a-4644d87672ef · outbound

This paper cites Differentiable graph module (dgm) for graph convolutional networks,.

Graph Structure Learning with Bi-level Optimization Differentiable graph module (dgm) for graph convolutional networks,

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:41:10.670289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.