Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T06:01:08.931447Z
Paper Citation Record · LEDGER
Inferring the Graph Structure of Images for Graph Neural Networks
As of 15 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2509.04677.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T06:01:08.874253Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T06:01:08.959205Z
Reference resolution
17 of 17 outbound references displayed
- verified exact0
- verified fuzzy14
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 2bce1fa6-d1b8-4539-afcc-eb63f2a1dce5 · outbound
This paper cites Inferring the Graph Structure of Images for Graph Neural Networks.
Inferring the Graph Structure of Images for Graph Neural Networks Inferring the Graph Structure of Images for Graph Neural Networks
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T06:01:08.965623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9fc03acf-2976-4ef8-af1b-d2e52086512a · outbound
This paper cites We first produce a row and column correlation graph using the method in [5, 6].
Inferring the Graph Structure of Images for Graph Neural Networks We first produce a row and column correlation graph using the method in [5, 6]
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.129887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 760c4f51-db45-4005-85f0-1eceba00d42a · outbound
This paper cites Both datasets have 70,000 images with 60,000 im- ages for training and 10,000 for testing.
Inferring the Graph Structure of Images for Graph Neural Networks Both datasets have 70,000 images with 60,000 im- ages for training and 10,000 for testing
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.109908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e5da0ad2-ceca-4824-beea-71ac00fc8fbe · outbound
This paper cites an unresolved cited work.
Inferring the Graph Structure of Images for Graph Neural Networks Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T06:01:09.100064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d480316e-b04b-4a8e-8c60-2ea5f95024b0 · outbound
This paper cites We achieve this by inferring the underlying graph for im- ages using the correlation method in [5, 6].
Inferring the Graph Structure of Images for Graph Neural Networks We achieve this by inferring the underlying graph for im- ages using the correlation method in [5, 6]
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.090379Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation deead37f-9b20-4b19-a391-f518402a0dfd · outbound
This paper cites an unresolved cited work.
Inferring the Graph Structure of Images for Graph Neural Networks Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T06:01:09.120242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 686c802f-e02d-4f0c-b462-92c529620d1d · outbound
This paper cites Semi-supervised classi- fication with graph convolutional networks,.
Inferring the Graph Structure of Images for Graph Neural Networks Semi-supervised classi- fication with graph convolutional networks,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.080774Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9e3d06d3-a0f1-426c-b058-4c59732c9d30 · outbound
This paper cites Topology adaptive graph convolutional networks,.
Inferring the Graph Structure of Images for Graph Neural Networks Topology adaptive graph convolutional networks,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.071213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 240d8c0c-13f8-4724-a140-f42d4106b792 · outbound
This paper cites Graph attention networks,.
Inferring the Graph Structure of Images for Graph Neural Networks Graph attention networks,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.061188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3c5461fa-65cb-475c-9473-5e3a4a8aef88 · outbound
This paper cites Can classic gnns be strong baselines for graph-level tasks? simple architectures meet excellence,.
Inferring the Graph Structure of Images for Graph Neural Networks Can classic gnns be strong baselines for graph-level tasks? simple architectures meet excellence,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.051642Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 956b1cf0-5de1-4388-b02b-b985eada402f · outbound
This paper cites Learning the causal structure of networked dynam- ical systems under latent nodes and structured noise,.
Inferring the Graph Structure of Images for Graph Neural Networks Learning the causal structure of networked dynam- ical systems under latent nodes and structured noise,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.041670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ef55a910-2c90-4a33-8773-891772784d37 · outbound
This paper cites Inferring the graph of networked dynamical sys- tems under partial observability and spatially colored noise,.
Inferring the Graph Structure of Images for Graph Neural Networks Inferring the graph of networked dynamical sys- tems under partial observability and spatially colored noise,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.031696Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 176d46a3-5e0a-4e5c-ad0c-835149260990 · outbound
This paper cites Graph convolutional networks for image classification: Comparing approaches for building graphs from images,.
Inferring the Graph Structure of Images for Graph Neural Networks Graph convolutional networks for image classification: Comparing approaches for building graphs from images,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.020950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation bc9bbf99-5067-4254-8aed-360184238656 · outbound
This paper cites Slic superpixels,.
Inferring the Graph Structure of Images for Graph Neural Networks Slic superpixels,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:09.009880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5b323619-d3c3-4fc8-96d2-1616bee83bda · outbound
This paper cites Discrete signal processing on graphs,.
Inferring the Graph Structure of Images for Graph Neural Networks Discrete signal processing on graphs,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:08.999314Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a577d13d-3e68-466a-8c26-3e32494b31b5 · outbound
This paper cites Graph signal processing: Overview, challenges, and applications,.
Inferring the Graph Structure of Images for Graph Neural Networks Graph signal processing: Overview, challenges, and applications,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:08.988072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6f509ea7-b924-452e-b9f2-9b36dc30ffcd · outbound
This paper cites Graph signal processing: The 2d companion model,.
Inferring the Graph Structure of Images for Graph Neural Networks Graph signal processing: The 2d companion model,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T06:01:08.976781Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Pith citing papers
Observation 2bce1fa6-d1b8-4539-afcc-eb63f2a1dce5 · inbound
Inferring the Graph Structure of Images for Graph Neural Networks cites this paper.
Inferring the Graph Structure of Images for Graph Neural Networks Inferring the Graph Structure of Images for Graph Neural Networks
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T06:01:08.965623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.