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Paper Citation Record · LEDGER

Molecular geometry prediction using a deep generative graph neural network

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.00314.

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

pith.paper-citation-record.v1
1904.00314 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:36:08.312637Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T21:10:33.138913Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a5fc1505-1d30-45fc-9442-2251465fc464 · inbound

Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures cites this paper.

Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures Molecular geometry prediction using a deep generative graph neural network

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T05:36:08.312637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:36:08.312637Z digest=sha256:af30bcd3ca134b1cdb585a8c536ffe17b238f91d86b04c6a83927f41813f986d

Observation 4190f574-4c30-4003-b189-09ff4e06ac54 · inbound

Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data cites this paper.

Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data Molecular geometry prediction using a deep generative graph neural network

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-10T21:10:33.151882Z

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=2026-08-10T21:10:32.302181Z digest=sha256:9f5aaec4fcb1acf12ede8c39b2bdc82fcb4cde50d82030075e8329db8396764a