Pith. sign in

Paper Citation Record · LEDGER

Molecular Contrastive Learning of Representations via Graph Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2102.10056.

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

pith.paper-citation-record.v1
2102.10056 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:26:38.425760Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:08:56.303410Z

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 627245dc-95eb-46ef-848a-6e56b5192c1f · inbound

Handling Feature Heterogeneity with Learnable Graph Patches cites this paper.

Handling Feature Heterogeneity with Learnable Graph Patches Molecular Contrastive Learning of Representations via Graph Neural Networks

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:08:56.305521Z

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=pdf_text observed=2026-06-27T01:36:45.977332Z digest=sha256:5d05821ac554109e9c70548b51536a2ae122682905172a949ed7255d781cba8b

Observation 8e1fa422-9050-4713-821d-1be7b58923ef · inbound

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density cites this paper.

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density Molecular Contrastive Learning of Representations via Graph Neural Networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T22:26:38.425760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:26:38.425760Z digest=sha256:a70db6f0a3a60d3ed23a5e3467f428c5a20bbc338366581940209904b1fb1e42