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Paper Citation Record · LEDGER

Graph-based Molecular Representation Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2207.04869.

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

pith.paper-citation-record.v1
2207.04869 v3

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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:11:11.974349Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T01:00:51.473900Z

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 5326b85d-f1a8-4d82-85ef-fed7e8f485ff · inbound

Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond cites this paper.

Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Graph-based Molecular Representation Learning

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T20:11:11.974349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:11:11.974349Z digest=sha256:da63bfc65e40a9b0a7a0d06792c261b0e9bcfae72bd30936acedbf7b7c712b69

Observation a81c90c9-dcec-415f-adae-2652787bee14 · inbound

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence cites this paper.

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence Graph-based Molecular Representation Learning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-20T15:18:25.305866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T15:17:23.832754Z digest=sha256:dbdd141d520c41975417926587d9329e0219c752860e99ede2180570e616f5cb

Observation 316e47f5-4139-4ef5-be37-7f9a2eb79dbb · inbound

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence cites this paper.

Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence Graph-based Molecular Representation Learning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-22T01:00:51.477550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-22T00:58:31.100417Z digest=sha256:bc625f50060a87e998dd86c794bef9d04585f787b152a6b97768ede9b8a38932

Observation 890001eb-8e03-491a-8012-d01b47f44597 · inbound

Hypothesis-and-Refinement Learning of Organic Structures from Multimodal Spectroscopic Data cites this paper.

Hypothesis-and-Refinement Learning of Organic Structures from Multimodal Spectroscopic Data Graph-based Molecular Representation Learning

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-01T11:44:16.299468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T11:44:16.299468Z digest=sha256:d4aa0b2b345deca973e26b15dd10f672588ba80c3b9f5981e41afb0bf1e05832

Observation af9cabfa-e686-4e6d-a78e-0d6ba4856359 · inbound

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning cites this paper.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Graph-based Molecular Representation Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-07-31T18:33:45.124649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T18:33:45.124649Z digest=sha256:25e30ace05cdd5af5608dfd60562fae74899e5d9ac298d8a8f359dd834e2df92