Paper Citation Record · LEDGER

A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.08703.

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

pith.paper-citation-record.v1
2402.08703 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:40:22.418861Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:54:44.707589Z

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 1d2feed6-bdf9-4413-a543-aff463c8607d · inbound

AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusion cites this paper.

AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusion A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T20:40:22.418861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7560871-4832-41bf-9f3b-46dd02d2fc30 · inbound

Active Learning-Guided Seq2Seq Variational Autoencoder for Multi-target Inhibitor Generation cites this paper.

Active Learning-Guided Seq2Seq Variational Autoencoder for Multi-target Inhibitor Generation A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T19:45:23.566182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6d496a0-5ecc-44db-a1d7-b64f314bf059 · inbound

Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data cites this paper.

Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

Reference 78

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:54:44.714917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bde56735-9476-488d-af7d-a52e9d2c2f51 · inbound

Rethinking Scientific Discovery in the Agentic Era cites this paper.

Rethinking Scientific Discovery in the Agentic Era A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-11T23:26:06.516204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.