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Paper Citation Record · LEDGER

Genetic algorithms are strong baselines for molecule generation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.09267.

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

pith.paper-citation-record.v1
2310.09267 v1

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 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:07:58.221964Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:14:25.546884Z

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 aed08a07-8c39-4f49-b40d-9116533decc3 · inbound

NovoMolGen: Rethinking Molecular Language Model Pretraining cites this paper.

NovoMolGen: Rethinking Molecular Language Model Pretraining Genetic algorithms are strong baselines for molecule generation

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-05T19:07:58.221964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:07:58.221964Z digest=sha256:9f54b43f3041fa11e9cfd208476dd7865545860e08f748d3529ce5680020f77e

Observation b64bdb9a-559f-4496-b7db-0acaa22b84ba · inbound

NMR-Solver: Automated Structure Elucidation via Large-Scale Spectral Matching and Physics-Guided Fragment Optimization cites this paper.

NMR-Solver: Automated Structure Elucidation via Large-Scale Spectral Matching and Physics-Guided Fragment Optimization Genetic algorithms are strong baselines for molecule generation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T13:29:34.327107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:29:34.327107Z digest=sha256:0f0adae355168bbf40a878839926f9014b0c35a08376bc31ad3ade4bde47d7b5

Observation 4ad94bf1-9f73-47a7-98ca-723b5b9890e0 · inbound

GLACIER: Rethinking Mass Spectrum Prediction as an Object Detection Problem cites this paper.

GLACIER: Rethinking Mass Spectrum Prediction as an Object Detection Problem Genetic algorithms are strong baselines for molecule generation

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:14:25.549115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-30T08:11:04.377613Z digest=sha256:7d16c51c30b0e39be84ccbeb524d0b738fdd1cdbacff23d352a719db899e2a49

Observation 9fd11b40-6626-47fc-8c6f-6b6f751abdba · inbound

Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark cites this paper.

Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark Genetic algorithms are strong baselines for molecule generation

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:54:20.757505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-30T06:47:54.094083Z digest=sha256:a7b6cb5354fb0c33852491a9cfca577d5c684a1aa43ac7ddef595d6f4369d5a6

Observation a72a7859-f500-41ca-b9ed-cd991c891b0d · inbound

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation cites this paper.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Genetic algorithms are strong baselines for molecule generation

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-01T13:39:13.434988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T13:39:13.434988Z digest=sha256:7d72b7f939d5ec68e344ae985ea167a4fd0b34fe31bef54ea6c20ebbb13353cd