Paper Citation Record · LEDGER

Scalable Generative Modeling of Weighted Graphs

As of 17 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2507.23111.

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

pith.paper-citation-record.v1
2507.23111 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:11:24.673133Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T19:40:22.845288Z

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 exact0
verified fuzzy4
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8c44a39-8d18-467f-8a6e-e112c346ba76 · outbound

This paper cites Importantly, the summary state for each row is independent of those for other rows, allowing these computations to be performed in parallel.

Scalable Generative Modeling of Weighted Graphs Importantly, the summary state for each row is independent of those for other rows, allowing these computations to be performed in parallel

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:11:24.865604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 12ac0e34-d8ca-4447-92e7-f125323ae407 · outbound

This paper cites an unresolved cited work.

Scalable Generative Modeling of Weighted Graphs Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:11:24.851751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8ea5a07f-3d6d-4872-b2e8-fcf41ea6c32d · outbound

This paper cites an unresolved cited work.

Scalable Generative Modeling of Weighted Graphs Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:11:24.838075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bbe60325-a193-4791-8074-a88ba90bed62 · outbound

This paper cites Finally, we note that for graph generation, the treesTu must be constructed sequentially.

Scalable Generative Modeling of Weighted Graphs Finally, we note that for graph generation, the treesTu must be constructed sequentially

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:11:24.823487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f2617283-9fab-4656-a92d-27d98c710297 · outbound

This paper cites an unresolved cited work.

Scalable Generative Modeling of Weighted Graphs Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:11:24.810171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 16d08213-fdc9-4093-9dc9-f848acf33766 · outbound

This paper cites an unresolved cited work.

Scalable Generative Modeling of Weighted Graphs Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:11:24.795794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 516e8079-6cc1-4fee-8b56-83350410e00a · outbound

This paper cites an unresolved cited work.

Scalable Generative Modeling of Weighted Graphs Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:11:24.781297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 72c41172-6d59-47a7-85a7-28eeb7628da2 · outbound

This paper cites an unresolved cited work.

Scalable Generative Modeling of Weighted Graphs Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:11:24.767569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 81ad39ea-a604-4ea5-b3a5-49488a08de8c · outbound

This paper cites Next, an application of iterative expectation and variance yield the mean and variance of weights pooled from all trees as.

Scalable Generative Modeling of Weighted Graphs Next, an application of iterative expectation and variance yield the mean and variance of weights pooled from all trees as

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:11:24.753621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4c4e6bb7-c841-4471-90b9-47285e48db28 · outbound

This paper cites an unresolved cited work.

Scalable Generative Modeling of Weighted Graphs Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:11:24.739579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5361e662-d3f8-42ad-8433-f39c51d413af · outbound

This paper cites 23 A.5 Further Training Details Hyperparameters For Adj-LSTM, node states were parameterized with a hidden dimension of 128 and use a 2-layer LSTM.

Scalable Generative Modeling of Weighted Graphs 23 A.5 Further Training Details Hyperparameters For Adj-LSTM, node states were parameterized with a hidden dimension of 128 and use a 2-layer LSTM

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:11:24.725606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 221113f0-cb93-4a38-9b9a-9f2e8a686b37 · outbound

This paper cites Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations.

Scalable Generative Modeling of Weighted Graphs Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations

Reference 1997

Resolution: unresolved; no resolver link, observed 2026-08-06T11:11:24.625791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 8d77c1bb-a8af-4f35-aaf1-d22cce3d5dbf · inbound

TVGL-CFM:Generating and Forecasting Time-Varying Trajectories of Dynamic Networks with Conditional Flow Matching cites this paper.

TVGL-CFM:Generating and Forecasting Time-Varying Trajectories of Dynamic Networks with Conditional Flow Matching Scalable Generative Modeling of Weighted Graphs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T19:40:22.845288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.