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Paper Citation Record · LEDGER

Graph-based Molecular Representation Learning

As of 8 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 2026-08-08T06:32:00.761636+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:e9806227f79a74ee2b7dfa8fdf7d70e419554d1315a65837086b40890b9bd936

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T15:17:23.832754Z digest=sha256:1887977c6f2b0cf06165eed4c85518b1ea992a5902a8226bccd29a3804702c42

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-22T00:58:31.100417Z digest=sha256:0c3ea61d89aef51c111aa23508d8b03a365b0f8e45ad62710b24ac00b40691b0

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:ee82d7a45e8509e72931364fc3ca9ce0ab5adba58d7b0b92de639d7ae99f4b4f

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=sha256:42d5217ed2c4372c8819f9052653e862fb47a2f42beaa67489fff5d7d391f591