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Paper Citation Record · LEDGER

DAG-GNN: DAG Structure Learning with Graph Neural Networks

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1904.10098.

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

pith.paper-citation-record.v1
1904.10098 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T09:09:30.695363Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

130
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation bdcf62ce-8db4-4f93-819e-161ee0693ba6 · inbound

Visual Analysis of Multi-outcome Causal Graphs cites this paper.

Visual Analysis of Multi-outcome Causal Graphs DAG-GNN: DAG Structure Learning with Graph Neural Networks

Reference 78

Resolution
verified exact
local_arxiv, observed 2026-05-23T22:43:32.217168Z

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.

source=pdf_text observed=2026-05-23T22:42:45.037653Z digest=sha256:2e5d79feffeffe1b18e2422f684e50ba269b5853e79227fea82e14890f56b0f4

Observation 4a21ce80-5051-4b33-85ec-ff59e023bd56 · inbound

Proactive Dialogue Model with Intent Prediction cites this paper.

Proactive Dialogue Model with Intent Prediction DAG-GNN: DAG Structure Learning with Graph Neural Networks

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:01:27.668679Z

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.

source=pdf_text observed=2026-05-07T08:31:16.300418Z digest=sha256:f8b707a59e14214c9ce683bf4b5fc917b865b7b9e5d221dfcd73b730f22ee0af

Observation 9a22dc84-d24e-41a5-a4c7-604874db0aa6 · inbound

Prognostic Value of Lung Ultrasound Biomarkers for Readmission Risk in Congestive Heart Failure: A Pilot Data-Driven Analysis cites this paper.

Prognostic Value of Lung Ultrasound Biomarkers for Readmission Risk in Congestive Heart Failure: A Pilot Data-Driven Analysis DAG-GNN: DAG Structure Learning with Graph Neural Networks

Reference 246

Resolution
verified exact
local_arxiv, observed 2026-05-20T15:43:26.301620Z

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.

source=arxiv_source observed=2026-05-20T15:41:31.181025Z digest=sha256:b703ed994a00a286c6b73f515c9702c519fbed1956c51d095bacb97557a25a77

Observation a8139332-7c69-4ce7-83c5-6d1035f8af32 · inbound

Do Real-World Datasets Contain Natural Experiments? An Empirical Study Using Causal Feature Selection cites this paper.

Do Real-World Datasets Contain Natural Experiments? An Empirical Study Using Causal Feature Selection DAG-GNN: DAG Structure Learning with Graph Neural Networks

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-06-28T10:01:52.568276Z

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.

source=pdf_text observed=2026-06-28T09:57:53.889935Z digest=sha256:5f0f95cf23fe25668fbd7dcdf13d30bcee16dc7f65dd9173f707a3ee0cf987eb

Observation 56fb8829-1123-4a0e-86eb-c7c51355effa · inbound

A Neuroimaging Simulation Framework for Developing and Evaluating Causal AI cites this paper.

A Neuroimaging Simulation Framework for Developing and Evaluating Causal AI DAG-GNN: DAG Structure Learning with Graph Neural Networks

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-06-30T13:24:40.777013Z

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.

source=pdf_text observed=2026-06-30T09:09:30.695363Z digest=sha256:cb94ad69046735453fc0c9489912acf5d37f43d2e8a099df0a76941c2ca0ac19