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Paper Citation Record · LEDGER

Deep Reinforcement Learning for Inverse Inorganic Materials Design

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2210.11931.

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

pith.paper-citation-record.v1
2210.11931 v1

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:16:56.260076Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T11:07:48.500593Z

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 d1069d32-ddec-4311-9056-9b2711d84cc8 · inbound

MOFGPT: Generative Design of Metal-Organic Frameworks using Language Models cites this paper.

MOFGPT: Generative Design of Metal-Organic Frameworks using Language Models Deep Reinforcement Learning for Inverse Inorganic Materials Design

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T12:16:56.260076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:16:56.260076Z digest=sha256:fdbe78aef790ec3ebdf265f98c87d14cfa60af9fcbe276d2b7a4ec99c8203f2d

Observation 8f5e4f8e-06cf-4528-aadb-f970c46786ef · inbound

Extended Factorization Machine Annealing for Rapid Discovery of Transparent Conducting Materials cites this paper.

Extended Factorization Machine Annealing for Rapid Discovery of Transparent Conducting Materials Deep Reinforcement Learning for Inverse Inorganic Materials Design

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-06T11:07:48.661650Z

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=pdf_text observed=2026-08-06T11:07:46.535523Z digest=sha256:e6a56cc13aad417697b71c90c6a756e33b14486499a3b61751e30b334e3d2f43